Agent skill

Opc

by iamtouchskyer in iamtouchskyer/opc

OPC — One Person Company. An agent skill from iamtouchskyer/opc.

MITAuto-check: warningsAgent Workflows

Install Opc

The automated check flagged lines worth reading first. See the safety section below.

skills CLI
$ npx skills add iamtouchskyer/opc --skill opc -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install iamtouchskyer/opc opc --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
opc
GitHub stars
197
Token cost
~9.2k tokens
SKILL.md length
3,845 words
Files
309 (incl. scripts)
Skills in repo
1
Repo updated
First seen
Licence
MIT

At a glance

OPC — One Person Company. An agent skill from iamtouchskyer/opc.

  • Works in 3 steps: Run opc-harness ls to discover active… → If .harness/ has wave-* files but no… → Otherwise → fresh start.
  • Tasks that involve Brainstorming
  • SKILL.md covers Invocation, Task Inference + Flow Selection, Flow Templates and Getting Started, plus 4 more sections
  • Runs JavaScript and Shell scripts from its folder; calls node, python3 and npm

What it does

Opc is an agent skill from iamtouchskyer/opc. OPC — One Person Company. Digraph-based task pipeline with independent multi-role evaluation. Builds, reviews, analyzes, and brainstorms with specialist agents. Every path ends with evaluation. /opc <task, /opc -i <task, /opc <role [role...]

Its SKILL.md is about 9.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 313 other files, including scripts (for example `.github/workflows/ci.yml`, `CHANGELOG.md` and `CONTRACTS.md`).

It sits in Agent Workflows, covering Brainstorming. The repository describes itself as: OPC — One Person Company. A full team in a single Claude Code skill. Adaptive agent orchestrator with 21 built-in roles, 6 flow templates, and adversarial quality control. The licence is MIT.

When your agent uses it

  • Tasks that involve Brainstorming

Example prompts

  • “/opc”

Requirements

  • Node.js
  • A Bash shell

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Run opc-harness ls to discover active flows. If any exist for the current project, show them and ask whether to resume or start fresh.
  2. If .harness/ has wave-* files but no flow-state.json → legacy v0.4.x format detected. Print: "Detected v0.4.x .harness/ format. Please…
  3. Otherwise → fresh start.

What it can do on your machine

Read from SKILL.md and the folder at commit f36f483. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (JavaScript and Shell, from the files we listed), which the agent can run.

    Shell commands in SKILL.md call:

    • node
    • python3
    • npm

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npm, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Opc loads about 9.2k tokens when it runs. Until then it costs about 62 tokens; SKILL.md has 3,845 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~62
When it runs · the whole SKILL.md, loaded when a task matches
~9.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: warnings

The automated check found patterns that need a careful read before installing.

  • WarningContains instruction-override wording (e.g. “without asking the user”)SKILL.md:485
    nd offer escape options. Never continue without user consent.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from iamtouchskyer/opc at commit f36f483, republished under its MIT licence (© iamtouchskyer). 3,845 words, ~9,181 tokens.

Download SKILL.mdSave it as .claude/skills/opc/SKILL.md (or your agent's skills folder). This skill also uses 308 other files; get the full folder from GitHub.
name
opc
description
OPC — One Person Company. Digraph-based task pipeline with independent multi-role evaluation. Builds, reviews, analyzes, and brainstorms with specialist agents. Every path ends with evaluation. /opc <task>, /opc -i <task>, /opc <role> [role...]
version
0.10.2

OPC — One Person Company

One principle: the agent that does the work never evaluates it.

A full team in a single skill. The digraph engine handles any task — building code, reviewing code, analyzing problems, brainstorming designs. It infers which flow and entry point to use from the task itself, and every path ends with independent evaluation.

Invocation

Harness path: The opc-harness binary lives at bin/opc-harness.mjs relative to this skill's install directory. Resolve it once at session start:

bash
OPC_HARNESS="$HOME/.claude/skills/opc/bin/opc-harness.mjs"

All opc-harness references below mean node "$OPC_HARNESS". Set this as a shell variable and reuse it throughout the session.

/opc <task>              # auto mode — infer flow and roles from the task
/opc -i <task>           # interactive mode — ask questions before dispatch
/opc <role> [role...]    # explicit roles — skip role selection, dispatch directly
/opc loop <task>         # autonomous loop — decompose, schedule cron, run 24h unattended
/opc skip                # skip current node, advance via PASS edge
/opc pass                # force-pass current gate
/opc stop                # terminate flow, preserve session state
/opc goto <nodeId>       # manual jump to a node (cycle limits still enforced)

Task Inference + Flow Selection

The orchestrator reads the task, selects a flow template, and determines the entry point.

Task says...Flow templateDefault entry
"review", "audit", "check", "before we merge", "找问题", "开源前看看"reviewreview
"analyze", "diagnose", "what's wrong with", "分析"reviewreview
"build", "implement", "create", "fix bug", "帮我实现", "重构成..."build-verifybrief
"quick fix", "small change", "one-liner", "patch", "trivial fix", "快速修复", "小改动"quickbuild
"brainstorm", "explore options", "what are the approaches", "有什么方案"build-verifybrief
"plan", "decompose", "break this down", "scope", "estimate", "拆一下"build-verifybrief
"verify", "test", "QA", "check before release", "发布前验收"pre-releaseacceptance
"post-release", "user test", "onboarding check", "用户验收"pre-releaseacceptance
Complex, vague, or multi-keyword requestfull-stackdiscuss
/opc loop or multi-unit feature backlogloop-protocolplan decomposition

Entry override — user context can shift the entry point (only if target ∈ template nodes):

User has...Entry override
A vague idea or briefFirst node in template
A spec or design docbrief (if ∈ template), else build
An implementation planbrief (if ∈ template), else build
A qualified build-brief.md from prior runbuild (skip brief if lint passes)
Code/artifact that needs evaluationreview, code-review, or test-design (if ∈ template)
Everything done, needs acceptanceacceptance (if ∈ template)

Priority rules:

  • /opc loop <task> = enter autonomous loop mode. Follow ./pipeline/loop-protocol.md: first check .opc/runbooks/ for a matching runbook, otherwise decompose task into units. Initialize loop state, start cron, execute ticks. Each tick runs the appropriate OPC flow for that unit type.
  • /opc <role> [role...] without a task = review of current codebase using review flow with named roles.
  • /opc with no arguments = prompt user to describe their task.
  • If task matches multiple rows, prefer the flow that includes build — code changes must precede review.

Show triage result:

📌 Flow: {flow template name}
📍 Entry: {entry node}
⚡ Interaction: auto / interactive
Rationale: {1 sentence}

Override: If user explicitly names a task type, respect that. Users can adjust after seeing triage.

Flow Templates

Flow graph structures (nodes, edges, limits) are defined in opc-harness code. The orchestrator uses opc-harness route to determine next nodes — do not look up edges yourself.

Each template below describes which agents to dispatch at each node and which protocol to use.

legacy-linear

Equivalent to v0.4.x behavior. Used as internal fallback only.

NodeTypeAgentsProtocol
designdiscussion[planner]design exploration
planbuild[planner]task decomposition
buildbuild[implementer]implementer-prompt.md
evaluatereview[selected roles]role-evaluator-prompt.md
deliverbuild—commit + report
review
NodeTypeAgentsProtocol
reviewreview[selected roles]role-evaluator-prompt.md
gategate—gate-protocol.md

Gate loopback: FAIL/ITERATE → review (multi-round with prior findings as context). Review is not limited to code — it evaluates any artifact: architecture proposals, documents, strategies, products.

build-verify
NodeTypeAgentsProtocol
briefbrief[architect]brief-protocol.md
buildbuild[implementer]implementer-prompt.md
code-reviewreview[selected roles]role-evaluator-prompt.md
test-designreview[tester, + user/domain roles]test-design-protocol.md
test-executeexecute[orchestrator]executor-protocol.md
gategate—gate-protocol.md

test-design is a review node where multiple roles design test cases (API tests, E2E UI tests, edge cases) without executing them. test-execute runs the designed test plan and captures evidence. Principle: the person who decides what to test must not be the person who runs the tests.

quick
NodeTypeAgentsProtocol
buildbuild[implementer]implementer-prompt.md
reviewreview[selected roles]role-evaluator-prompt.md
test-designreview[tester, + user/domain roles]test-design-protocol.md
test-executeexecute[orchestrator]executor-protocol.md
gategate—gate-protocol.md

Scope: Non-UI, single-file or ≤3 file changes, low risk. If task involves UI/design, multi-module refactoring, or security-related changes → use build-verify instead. Gate loops back to build (no brief node), and quick still requires OPC-generated testCommand evidence before final PASS.

full-stack

The complete flow with discussion, multi-stage gates, and E2E verification.

NodeTypeAgentsProtocol
discussdiscussion[architect, engineer, tester]discussion-protocol.md
briefbrief[architect]brief-protocol.md
buildbuild[implementer]implementer-prompt.md
code-reviewreview[frontend, backend]role-evaluator-prompt.md
test-designreview[tester, + user/domain roles]test-design-protocol.md
test-executeexecute[orchestrator]executor-protocol.md
gate-testgate—gate-protocol.md
acceptancereview[pm, designer]role-evaluator-prompt.md
gate-acceptancegate—gate-protocol.md
auditreview[security, compliance, a11y]role-evaluator-prompt.md
gate-auditgate—gate-protocol.md
e2e-userexecute[new-user, active-user, churned-user]executor-protocol.md
gate-e2egate—gate-protocol.md
ux-simulationexecute[new-user, active-user, churned-user]ux-simulation-protocol.md + ux-observer-protocol.md
gate-finalgate—gate-protocol.md
pre-release
NodeTypeAgentsProtocol
acceptancereview[pm, designer]role-evaluator-prompt.md
gate-acceptancegate—gate-protocol.md
auditreview[security, compliance, a11y]role-evaluator-prompt.md
gate-auditgate—gate-protocol.md
e2e-userexecute[new-user, active-user, churned-user]executor-protocol.md
gate-e2egate—gate-protocol.md

Getting Started

Before task inference, check for existing state:

  1. Run opc-harness ls to discover active flows. If any exist for the current project, show them and ask whether to resume or start fresh.
  2. If .harness/ has wave-* files but no flow-state.json → legacy v0.4.x format detected. Print: "Detected v0.4.x .harness/ format. Please delete .harness/ and re-run, or manually migrate." Do not proceed.
  3. Otherwise → fresh start.

After flow selection, initialize with the matching interaction mode:

bash
opc-harness init --auto --claude-session-id "${CLAUDE_SESSION_ID}" --flow {TEMPLATE} --entry {ENTRY_NODE}
opc-harness init --flow {TEMPLATE} --entry {ENTRY_NODE} # interactive (`/opc -i`) only

Auto init requires the installed OPC PreToolUse hook. Interactive init does not create a Claude session registry and is not subject to the node or repair-edge circuit breaker.

Init auto-creates ~/.opc/sessions/{project-hash}/{session-id}/ and updates the latest symlink. All subsequent harness commands automatically resolve to the latest session dir — you do NOT need to pass --dir or capture the output. Just run commands normally:

bash
opc-harness route --node review --verdict PASS --flow {TEMPLATE}
opc-harness transition --from review --to gate --verdict PASS --flow {TEMPLATE}
opc-harness viz --flow {TEMPLATE}

Multi-window safety: Each init creates a new session dir. If multiple OPC windows run on the same project, the last one to init becomes latest. To pin a specific session, pass --dir <path> explicitly.

Backward compat: Pass --dir .harness to init for a project-local harness dir.

Show flow graph — immediately after init, run opc-harness viz --flow {TEMPLATE} and display the ASCII output to the user. This gives them a visual map of the entire flow before execution begins.

Before starting, extract acceptance criteria — 3-7 concrete, testable bullet points. Evaluators grade against these.

Agent Model Routing — Mandatory Pre-Flight

Flow topology and model tier are independent. Keep every selected node, round, and role, but before each Agent call run:

bash
opc-harness model-route --node {NODE_ID} --node-type {NODE_TYPE} [--role {ROLE}] --dir {PROJECT_ROOT}

Pass the returned model through the host's per-dispatch selector. dispatch: false means no Agent. On an error or unsupported selector, stop instead of silently inheriting the root model. Re-run with --allow-premium only after explicit user approval. Show 💰 Model route: {tier} → {model} ({source}) before launch. Read ./pipeline/model-routing.md only for configuration or troubleshooting.

Quality Tier Selection — Mandatory Pre-Flight

Before the Definition of Done questions, the orchestrator MUST select a quality tier. See ./pipeline/quality-tiers.md for full definitions.

TierWhenBaseline
functionalCLI, API, backend, library, infraNo UI craft requirements
polishedUI, frontend, website, dashboard, docsDark/light, responsive, loading/error/empty states, favicon, focus styles
delightfulShowcase, demo, pitch, consumer productAll of polished + transitions, animations, micro-interactions, onboarding

Selection rules:

  1. User explicitly specifies tier → use it
  2. Task involves UI/frontend → default polished
  3. Task is CLI/API/backend → default functional
  4. Task includes "showcase", "demo", "pitch", "delightful", "beautiful" → delightful
  5. Interactive mode → ask the user

Show tier selection:

🎯 Quality Tier: {tier}
   Baseline: {N items from tier checklist}

The tier's baseline checklist items are automatically appended to acceptance criteria under a "## Quality Baseline ({tier})" section in acceptance-criteria.md (in the session dir). The implementer and evaluator both receive the tier as context.

Definition of Done — Mandatory Pre-Flight (all modes)

Before dispatching ANY work, the orchestrator MUST establish a clear definition of done. This applies to both auto and interactive modes — the only difference is how the answers are obtained (inferred vs asked).

Three questions that must have answers before the first node executes:

  1. What does "done" look like? — Concrete, observable outcomes. Not "implement auth" but "user can log in with email/password, session persists across refresh, logout clears session."

  2. How will we verify it? — Map each outcome to a verification method:

    • Code change → which tests? (npm test, specific test file, new test to write?)
    • UI change → which page/component to screenshot? What should be visible?
    • API change → which endpoint to curl? What response shape?
    • Refactor → which existing tests must still pass?
  3. How will we evaluate quality? — What should reviewers look for beyond "it works"?

    • Performance constraints? ("page load < 2s")
    • Security concerns? ("no PII in logs")
    • Compatibility? ("works in Safari")
    • Edge cases? ("handles empty input, 10k items, unicode")

In auto mode: infer answers from the task description + codebase context (package.json scripts, existing tests, CLAUDE.md rules). Show inferred answers to user for confirmation. If task is too vague to infer concrete verification methods → ask, even in auto mode. A vague task is worse than a 30-second clarification.

In interactive mode (-i): ask directly, grouped with role-specific questions.

In loop mode (/opc loop): these answers go into plan.md per unit, so every tick knows how to verify itself even after context compaction.

Write the finalized acceptance criteria to acceptance-criteria.md (in the session dir) and include them in every subagent prompt.

Design Reproduction Pre-Flight: When the task involves reproducing/replicating a visual design from a reference image (keywords: 复刻, replicate, reproduce, reference image, 参考图, design reproduction), the orchestrator MUST run these additional init steps:

  1. Detect reference image — user provides a path (e.g., /Users/.../ref.jpg). Confirm the file exists.
  2. Extract design spec — run analyze_reference.py to generate a structured spec:
    bash
    python3 ~/.claude/skills/image-x/scripts/analyze_reference.py <ref_image> --output <session_dir>/spec.json
  3. Write ## Reference section in acceptance-criteria.md:
    markdown
    ## Reference
    - reference_image: /absolute/path/to/ref.jpg
    - design_spec: /absolute/path/to/session/spec.json
  4. Set quality baseline for design reproduction:
    markdown
    ## Quality Baseline (polished)
    - design-diff overall ≥ 4.0
    - zero major diffs

This enables the full automated loop: build reads spec.json → implementer produces HTML → test-execute screenshots + VLM design-diff → gate reads diffs → ITERATE feeds diffs back to build. See ./pipeline/executor-protocol.md § "Design Reproduction Mode" for test-execute details.

Criteria Lint — Mandatory Gate: After writing acceptance-criteria.md, run opc-harness criteria-lint acceptance-criteria.md (use the session dir path). If it fails, revise and re-run (max 3 auto-fix attempts in auto mode, user-driven in interactive mode). See ./pipeline/criteria-lint.md for the mechanical checks. Init is gated — opc-harness init refuses to start if criteria-lint hasn't passed.

Task Scope — Mandatory for Loop Mode

In loop mode, every plan.md MUST include a ## Task Scope section listing the user's original requirements:

markdown
## Task Scope
- SCOPE-1: Backend API for user auth
- SCOPE-2: Frontend login page with form validation
- SCOPE-3: Browser E2E tests covering login flow
- SCOPE-4: Unit tests with 100% coverage on new code

The harness enforces this mechanically:

  • init-loop refuses to start if ## Task Scope is missing (bypass: --skip-scope)
  • complete-tick on the final tick checks that every SCOPE-N item was covered by at least one completed unit (keyword overlap or explicit reference). Uncovered items = hard error, pipeline cannot complete (bypass: --skip-scope-check)
  • next-tick termination output includes uncovered_scope if any items lack coverage

This prevents the #1 failure mode: LLM decomposition misses part of the original task, pipeline declares "complete" while major scope items are untouched.

Interactive Mode Details (with -i)

Ask targeted questions derived from selected roles — what does each role need that can't be inferred from the codebase? Aim for 3-5 grouped questions, merged with the Definition of Done questions above.

  • Engineering roles usually read code directly — no extra context needed.
  • Product and user roles benefit most: "Who are your target users?", "What's the product stage?"
  • Security and Compliance may need: "Do you handle PII?", "Target markets?"

Persona construction for user roles: In auto mode, infer from project context. In interactive mode, ask directly.

Project Context

Subagents don't inherit CLAUDE.md or project instructions automatically. When dispatching any subagent, forward relevant project context: dev workflow rules, precommit checks, coding conventions, test commands. Include this in every subagent prompt.

Superpowers Integration

If superpowers skills are available, use them: brainstorming for design, plan writing, subagent-driven development for build, and branch delivery.


Built-in Roles

Product:     pm, designer
User Lens:   new-user, active-user, churned-user
Engineering: frontend, backend, devops, architect, engineer
Quality:     security, tester, compliance, a11y
Specialist:  planner, user-simulator, devil-advocate

Role definitions live in roles/<name>.md. Add a .md file to roles/ to create a custom role.

Role Discovery

The orchestrator searches for role definitions in this order (later sources override earlier ones with the same filename):

  1. Built-in roles — roles/<name>.md in OPC's install directory
  2. Flow template roles — if the active flow template specifies rolesDir, scan _resolvedRolesDir/<name>.md. Custom roles with the same name as a built-in one take precedence for this flow.
  3. Dynamic roles — created on-the-fly during execution (see below)

How to check for custom roles: After opc-harness init, if the flow template was loaded from ~/.claude/flows/, check FLOW_TEMPLATES[template]._resolvedRolesDir. If it exists and is a directory, scan it for .md files and merge into the role pool.

Protocol discovery works the same way: if the flow template specifies protocolDir, protocols in _resolvedProtocolDir/<name>.md supplement or override built-in protocols in pipeline/.

Role Selection
  1. Tag filter — from the flow template, you know the node type. Map to stage tags:
Node typeStage tags
reviewreview
buildbuild
executeexecute, post-release, verification
discussionbrainstorm, plan, discussion
gate(no roles dispatched)

Read the tags: front matter from each roles/<name>.md. Keep only roles whose tags include at least one matching stage tag.

  1. Select from filtered pool — pick 2-5 roles with distinct angles. Read each candidate's "When to Include" section to decide relevance.
  • Mandatory roles always included — roles with mandatory: true in front matter are auto-included in every review node. The orchestrator cannot remove them. Currently: skeptic-owner.
  • Each dispatched agent must have a DISTINCT angle. If two would produce 80%+ overlapping output, pick one.
  • Not every task needs every role. A CSS fix doesn't need Security.
  • Devil's Advocate auto-inclusion: When a discussion node reaches Round 2 with near-unanimous agreement (all agents converge on the same approach), the orchestrator SHOULD include devil-advocate in a subsequent review pass. Consensus is a signal to challenge, not to proceed. For irreversible decisions (data deletion, public API contracts, destructive migrations), devil-advocate is MANDATORY.
  • If user specified roles explicitly, use those — skip tag filtering entirely.

Dynamic Role Creation: If the task requires expertise not covered by any candidate, create a role on-the-fly following the same format (Identity + Expertise + When to Include + Anti-Patterns). Write to $SESSION_DIR/nodes/{nodeId}/dynamic-role-{name}.md. Max 5 dynamic roles per flow run.

Show role selection:

📋 Agents:
- frontend [standard/sonnet] — <specific scope>
- tester [economy/haiku] — <specific scope>
...

Launching {N} agents...

Node Execution

Auto mode is bounded. Continue without confirmation only while node and repair-edge budgets remain. Normal graph limits and validation failures still apply.

When the circuit breaker trips, stop and report immediately. Do not retry or attempt recovery from the current Claude session. Recovery requires the user to run an existing opc-harness stop, goto, skip, or pass command from an external terminal.

The orchestrator uses cursor-based execution — flow-state.json.currentNode is the single pointer. No topological sort.

Show full SKILL.md (1,542 more words)Show less
Execution Loop
1. Read flow-state.json → currentNode
2. Look up currentNode in the flow template table above → get type, agents, protocol
3. Execute based on node type (see below)
4. After execution:
   - opc-harness validate → check handshake.json
   - Update progress.md with narrative line
   - opc-harness route --node {current} --verdict PASS --flow {template} → get next
   - opc-harness transition --from {current} --to {next} --verdict PASS --flow {template}
   - **Show flow viz**: run `opc-harness viz --flow {template}` and display to user
   - Loop back to step 1
5. When route returns next=null → flow complete → Deliver → **Prompt replay** (see below)
Node Type: discussion

Follow ./pipeline/discussion-protocol.md.

  1. Resolve a model route for every participant, then dispatch agents for 3 rounds. Round 1: parallel (agents are independent — no reason to serialize). Round 2: serial with context injection (each agent sees Round 1 outputs, writes diffs only). Round 3: facilitator convergence.
  2. Orchestrator writes handshake.json after collecting all artifacts (agents don't write it).
  3. Discussion nodes produce no verdict — the decision artifact feeds downstream.
Node Type: build

Follow ./pipeline/implementer-prompt.md in Build/Fix/Polish mode.

  1. Resolve the implementer's model route and dispatch it with the returned explicit model.
  2. Single agent → agent writes its own handshake.json.
  3. Multiple agents (parallel, with isolation: "worktree") → orchestrator merges artifacts and writes handshake.json.
  4. With superpowers: invoke superpowers:subagent-driven-development.
  5. After committing delivered code, run opc-harness record-commit --sha <sha> (or bare, defaulting to HEAD) so the terminal gate's changeScopeCoverage layer scopes to what this flow produced instead of a blind HEAD~1 diff. Skip only if the build committed nothing.
Node Type: review

Follow ./pipeline/role-evaluator-prompt.md.

  1. Select roles per Role Selection rules.
  2. Resolve a model route for each selected role, then dispatch evaluators — parallel if no dependencies, serial with context injection if dependencies exist.
  3. Each agent writes eval-{role}.md to $SESSION_DIR/nodes/{NODE_ID}/run_{RUN}/.
  4. Orchestrator writes handshake.json after all agents return, merging all eval files into artifacts[].
  5. Before dispatching, build context brief using ./pipeline/context-brief.md (for review/analysis tasks).

Critical — Review Independence:

  • Review MUST use independent subagents (Agent tool), never the orchestrator reviewing its own build output.
  • In loop mode, review MUST be a separate tick/unit from implementation. Never combine build + review in one tick.
  • The orchestrator MUST NOT filter, downgrade, or dismiss findings before writing the handshake. All findings pass through to the gate.
Node Type: execute

Follow ./pipeline/executor-protocol.md.

Executor nodes are executed by the orchestrator directly — not as a subagent. This is because executors need full tool access (Bash, Playwright, Skills).

  1. Smoke test tool availability.
  2. Execute acceptance criteria scenarios.
  3. Capture evidence (CLI output, screenshots).
  4. Orchestrator writes handshake.json with evidence artifacts.
  5. Handshake validation enforces: execute nodes must have evidence artifacts.
Node Type: gate

Follow ./pipeline/gate-protocol.md.

Gate nodes are executed by the orchestrator directly — no subagent dispatch.

  1. opc-harness synthesize --node {upstream} → get verdict.
  2. Mechanical validation (severity emojis, file refs, fix suggestions).
  3. opc-harness route --node {gate} --verdict {V} --flow {template} → get next node.
  4. opc-harness transition --from {gate} --to {next} --verdict {V} --flow {template} → validates edge, writes gate handshake, updates state.
  5. Notify user: pass/loopback/done/blocked.

Verdict & Loopback

Gate nodes produce verdicts via opc-harness synthesize (code, not LLM judgment):

  • Any 🔴 → FAIL
  • Any 🟡 → ITERATE
  • All 🔵/LGTM → PASS
  • Any BLOCKED → BLOCKED

Code enforces all limits:

  • maxLoopsPerEdge = 3 (same edge can't be traversed more than 3 times)
  • maxTotalSteps = 20-30 (depending on flow template)
  • maxNodeReentry = 5 (same node can't be entered more than 5 times)

Oscillation detection: After a loopback, run opc-harness diff on consecutive evaluations. If oscillation: true, surface to user.

Escape hatches:

  • /opc skip — skip current node, advance via PASS edge
  • /opc pass — force gate to PASS
  • /opc stop — terminate flow, preserve state
  • /opc goto <nodeId> — manual jump (cycle limits still enforced via transition)

When transition returns allowed: false → show the user why (which limit hit) and offer escape options. Never continue without user consent.


File-Based State

$SESSION_DIR/                    # ~/.opc/sessions/{hash}/{id}/ or .harness/ if --dir used
├── flow-state.json              # Current node, execution history, edge counts, limits
├── progress.md                  # Human-readable narrative log
└── nodes/
    └── {nodeId}/
        ├── handshake.json       # Machine-readable envelope (summary + verdict + artifact paths)
        └── run_{N}/
            ├── eval.md          # Single evaluator output (detailed findings)
            ├── eval-{role}.md   # Per-role evaluator output (multi-role)
            ├── round-1-{role}.md # Discussion round 1
            ├── round-2-{role}.md # Discussion round 2 (diffs only)
            ├── decision.md      # Discussion facilitator decision
            ├── screenshot-{N}.png  # Executor GUI evidence
            └── command-output-{N}.txt  # Executor CLI evidence

Relationships:

  • handshake.json = envelope. Its artifacts[] points to detailed files (eval.md, screenshots, etc.)
  • flow-state.json = sole source of truth for execution position and history
  • eval.md / eval-{role}.md = human-readable findings (read by synthesize to compute verdict)
  • progress.md = narrative projection of flow execution (for humans)

Prompt Templates

All templates live in ./pipeline/:

  • evaluator-prompt.md — Single generic evaluator
  • role-evaluator-prompt.md — Role-specific evaluator (review, analysis, brainstorm outputs)
  • implementer-prompt.md — Implementer (Build / Fix / Polish modes)
  • discussion-protocol.md — Multi-agent discussion (round-robin, 3 rounds, facilitator)
  • gate-protocol.md — Verdict aggregation + code-based routing + transition + findings disposition
  • executor-protocol.md — CLI/GUI execution with evidence requirements
  • test-design-protocol.md — Test case design (review node, multi-role test planning before execution)
  • loop-protocol.md — Autonomous multi-unit execution (plan decomposition → cron loop → auto-terminate)
  • handoff-template.md — Handshake.json specification
  • context-brief.md — Design context brief procedure
  • model-routing.md — Explicit per-node/per-role model selection and premium approval
  • report-format.md — Presentation templates + JSON schema + replay
  • quality-tiers.md — Tier definitions + baseline checklists + severity calibration
  • ux-simulation-protocol.md — UX simulation gate (red flag detection, delta comparison, ordinal tier fit)
  • ux-observer-protocol.md — UX observer dispatch (persona-based pattern observation, closed enum red flags)
  • criteria-lint.md — DoD mechanical lint (single-pass structure + content checks, pre-init gate)

External Flow Templates

Custom flows can be defined as JSON files in ~/.claude/flows/. The harness loads them at startup and merges them into the template registry. Built-in templates take precedence (external cannot override).

JSON schema:

json
{
  "nodes": ["discover", "build", "review", "gate"],
  "edges": {
    "discover": { "PASS": "build" },
    "build":    { "PASS": "review" },
    "review":   { "PASS": "gate" },
    "gate":     { "PASS": null, "FAIL": "build", "ITERATE": "build" }
  },
  "limits": { "maxLoopsPerEdge": 3, "maxTotalSteps": 20, "maxNodeReentry": 5 },
  "nodeTypes": {
    "discover": "discussion", "build": "build",
    "review": "review", "gate": "gate"
  },
  "softEvidence": true,
  "opc_compat": ">=0.10",
  "contextSchema": {
    "build": {
      "required": ["task"],
      "rules": { "task": "non-empty-string" }
    }
  }
}

Validation rules:

  • nodes, edges, limits are required
  • All edge sources and targets must be in nodes
  • nodeTypes values must be: discussion, build, review, execute, gate
  • opc_compat uses >=X.Y semver range (current harness compatibility: 0.10.0)
  • Prototype pollution names (__proto__, constructor, prototype) are rejected

Optional fields:

  • softEvidence: true — downgrades missing-evidence errors to warnings for execute nodes
  • contextSchema — per-node validation rules for flow-context.json
  • opc_compat — minimum harness version required

contextSchema rules:

  • non-empty-string — must be a non-empty string
  • non-empty-array — must be a non-empty array
  • non-empty-object — must be a non-empty plain object (not array)
  • positive-integer — must be a positive integer > 0

Harness Command Reference

All commands output JSON to stdout. Errors go to stderr. All output is machine-parseable.

Flow Commands
CommandUsageDescription
init--flow <tpl> [--entry <node>] [--dir <p>]Initialize flow state. Creates flow-state.json and node directories. Seeds baseSha (git floor) and empty producedCommits.
record-commit[--sha <sha>] [--dir <p>]Record a commit the flow produced into flow-state.producedCommits. Defaults to HEAD; dedups; fail-closed on invalid sha. The gate's changeScopeCoverage layer scopes to these commits.
route--node <id> --verdict <V> --flow <tpl>Get next node from graph edges. Returns {next, allowed}.
transition--from <n> --to <n> --verdict <V> --flow <tpl> --dir <p>Execute state transition. Validates edge, checks limits, writes gate handshake, enforces backlog.
validate<handshake.json>Validate handshake schema (required fields, evidence check for execute nodes).
validate-chain[--dir <p>]Validate entire execution path — checks all handshakes match history.
validate-context--flow <tpl> --node <id> [--dir <p>]Validate flow-context.json against contextSchema rules.
finalize[--dir <p>] [--strict]Finalize terminal node. Marks flow as completed.
viz--flow <tpl> [--dir <p>] [--json]Visualize flow graph (ASCII or JSON). Shows ▶ current, ✅ visited, ○ pending.
replay[--dir <p>]Export full replay data as JSON (flow state + handshakes + run artifacts).
Escape Hatches
CommandUsageDescription
skip[--dir <p>] [--flow <tpl>]Skip current node, advance via PASS edge. Writes skip handshake.
pass[--dir <p>]Force-pass current gate node. Only works on gate-type nodes.
stop[--dir <p>]Terminate flow, preserve state. Sets status to "stopped".
goto<nodeId> [--dir <p>]Manual jump to any node. Cycle limits still enforced.
ls[--base <p>]List all active flows (scans ~/.opc/sessions/ and project-local .harness* directories).
Eval Commands
CommandUsageDescription
verify<file>Parse evaluation markdown → JSON (severity counts, verdict, findings).
synthesize<dir> --node <id> [--run N] [--base <dir>] [--no-strict] [--iteration N]Merge all evaluations for a node → aggregate verdict. D2 compound gate enforced by default (≥3 layers → FAIL); --no-strict for shadow mode. --base validates file:line refs.
report<dir> --mode <m> --task <t>Generate full report JSON with presentation data.
diff<file1> <file2>Compare two evaluation rounds. Detects oscillation.
Loop Commands (Layer 2 — Zero Trust)
CommandUsageDescription
init-loop[--plan <file>] [--dir <p>]Initialize loop state from plan.md. Validates plan structure, detects test/lint scripts.
complete-tick--unit <id> --artifacts <a,b> [--description <text>] [--dir <p>]Complete tick with evidence. Validates artifacts per unit type, checks plan hash, overlap detection.
next-tick[--dir <p>]Get next unit. Checks stall/oscillation, returns {ready, unit, terminate}.
Transition Details

The transition command enforces:

  • Edge validation — only declared edges are allowed
  • Cycle limits — maxLoopsPerEdge, maxTotalSteps, maxNodeReentry
  • Idempotency — repeated identical transitions are silently accepted
  • Gate detection — uses nodeTypes[from] === "gate" (not name prefix)
  • Pre-transition validation — upstream handshake must exist and be valid
  • Backlog enforcement — if upstream has warnings, backlog.md must exist for FAIL/ITERATE transitions

Resilience

Agent spawn failures: Retry once. If it fails again, surface to user.

Context compaction resilience: opc install-hooks always registers the Node-based PreToolUse guard required by auto flows. When jq is available, it also registers optional PreCompact/PostCompact shell hooks that snapshot state and inject resume context after compaction. When auto-compact fires:

  1. PreCompact writes a resume brief to $SESSION_DIR/resume-brief.md
  2. PostCompact injects the brief as additionalContext into the new context
  3. The orchestrator sees the injection and resumes the flow automatically

If the optional compaction hooks are unavailable, flow-state.json still persists on disk, but the orchestrator must be manually re-invoked via /opc (which runs opc-harness ls to discover active flows).

State recovery: On resume, run opc-harness validate-chain. If inconsistent → surface to user, do not auto-repair.

Legacy detection: If .harness/ in project root has wave-* files but no flow-state.json → refuse to run. Print migration instructions.

Fresh context per agent. Always spawn new subagents. Files carry state; agents bring fresh capacity.


Flow Completion & Replay

When the flow completes (route returns next=null):

  1. Show final viz: opc-harness viz --flow {template}
  2. Show summary: total steps, nodes visited, any loopbacks, and dispatched agent counts by model tier
  3. Generate HTML report (use the session dir from init output, or find it via opc-harness ls):
    bash
    node "$OPC_HARNESS/../opc-report.mjs" --dir <session-dir> --output <session-dir>/report.html --title "{task summary}"
    This produces a self-contained dark-theme HTML report with mechanically parsed stats, pipeline visualization, findings tables, and R2 fix tracking. Open it for the user.
  4. Prompt the user:
    ✅ Flow complete! Report: $SESSION_DIR/report.html
    Want to see the replay? Run: /opc replay

© iamtouchskyer, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 308 other files (scripts) in the repository root of iamtouchskyer/opc.

  • SKILL.md
  • .github/workflows/ci.yml
  • .gitignore
  • CHANGELOG.md
  • CONTRACTS.md
  • CONTRIBUTING.md
  • INTEGRATION.md
  • LICENSE
  • README.md
  • bin/hooks/opc-post-compact.sh
  • bin/hooks/opc-pre-compact.sh
  • bin/hooks/opc-pre-tool-budget.mjs
  • bin/hooks/opc-pre-tool-budget.test.mjs
  • bin/lib/audit.mjs
  • bin/lib/brief-lint.mjs
  • bin/lib/bypass-args.mjs
  • … and 293 more

Open the folder on GitHubat commit f36f483

Compare with similar skills

Opc next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Opc compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Opc this skilliamtouchskyer/opc197—~9.2kAutomated safety check: WarnMIT
Brainstormingxpinjection/test-driven-spring-boot11254 repos~2.6kAutomated safety check: PassMIT
LLM Councilgcpdev/llm-council-skill4611 repos~1kAutomated safety check: NotesMIT
Typesafe AIOpenAgentsInc/openagents4559 repos~2.5kAutomated safety check: PassMIT
Yao Meta Skillyaojingang/yao-meta-skill2.7k—~768Automated safety check: PassMIT
Trellis StartROYIANS/foliq-print-template-designer1356 repos~646Automated safety check: PassMIT

Similar skills

  • Brainstorming

    xpinjection/test-driven-spring-boot

    You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior.

    112 GitHub starsUsed in 54 repos~2.6k tokens
    Agent WorkflowsAuto-check passed
  • LLM Council

    gcpdev/llm-council-skill

    Multi-LLM collaborative brainstorming and planning. An agent skill from gcpdev/llm-council-skill.

    461 GitHub starsUsed in 1 repo~1k tokens
    Agent WorkflowsAuto-check: notes
  • Typesafe AI

    OpenAgentsInc/openagents

    Build AI-powered software with TypeSafe: small units of AI intelligence you can use like programming primitives.

    455 GitHub starsUsed in 9 repos~2.5k tokens
    Agent WorkflowsAuto-check passed
  • Yao Meta Skill

    yaojingang/yao-meta-skill

    Create, improve, or evaluate an existing skill from workflows, prompts, SOPs, scripts.

    2.7k GitHub stars~768 tokensUpdated 1 mo ago
    Agent WorkflowsAuto-check passed
  • Trellis Start

    ROYIANS/foliq-print-template-designer

    Initializes an AI development session by reading workflow guides, developer identity, git status, active tasks, and project guidelines from .trellis/.

    135 GitHub starsUsed in 6 repos~646 tokens
    Agent WorkflowsAuto-check passed
  • Brainstorming Before Building

    jnMetaCode/superpowers-zh

    Turns a rough idea into an approved design before any code is written, sorting the request into spike, bounded or architectural and enforcing an approval gate.

    8.3k GitHub stars~1.8k tokensUpdated 3 days ago
    Agent WorkflowsAuto-check passed

Categories

Questions about Opc

What does Opc do?

OPC — One Person Company. An agent skill from iamtouchskyer/opc. Opc is an agent skill from iamtouchskyer/opc. OPC — One Person Company.

When should I use Opc?

Opc fits situations like: tasks that involve Brainstorming.

How do I install Opc in Claude Code?

Run `npx skills add iamtouchskyer/opc --skill opc -a claude-code`. Or copy the skill folder (the iamtouchskyer/opc repository) into .claude/skills/opc in your project. Claude Code loads it when a task matches its description.

How do I install Opc in Codex?

Run `npx skills add iamtouchskyer/opc --skill opc -a codex`. Or copy the skill folder (the iamtouchskyer/opc repository) into .agents/skills/opc in your project. Codex loads it when a task matches its description.

Can I use Opc in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add iamtouchskyer/opc --skill opc -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/opc, .gemini/skills/opc, .github/skills/opc and .opencode/skills/opc in your project.

What does Opc need to run?

Going by SKILL.md and its folder, Opc needs JavaScript and a shell for the scripts in its folder and the command-line tools its instructions call (node, python3 and npm). Our summary lists: Node.js; A Bash shell.

Does Opc access the network?

SKILL.md contains no URLs. Its commands use npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Opc safe to install?

Our automated static check of SKILL.md flagged 1 warning(s): contains instruction-override wording (e.g. “without asking the user”). Read the flagged lines before installing; the check is not a guarantee either way. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Opc use?

Opc is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Opc use?

About 9.2k tokens (SKILL.md is roughly 37k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Opc?

Skills that share tags, products or a category with Opc: Brainstorming (xpinjection/test-driven-spring-boot, 112 stars), LLM Council (gcpdev/llm-council-skill, 461 stars), Typesafe AI (OpenAgentsInc/openagents, 455 stars) and Yao Meta Skill (yaojingang/yao-meta-skill, 2.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Opc?

iamtouchskyer (a GitHub user) maintains it in iamtouchskyer/opc, which has 197 GitHub stars. The repository was last updated on September 8, 2026.

Source: iamtouchskyer/opc on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.