Agent skill

Repo Task Proof Loop

by DenisSergeevitch in DenisSergeevitch/repo-task-proof-loop

Repo-local workflow skill for large coding tasks. An agent skill from DenisSergeevitch/repo-task-proof-loop.

Apache-2.0Auto-check passedAgent Workflows

Install Repo Task Proof Loop

skills CLI
$ npx skills add DenisSergeevitch/repo-task-proof-loop --skill repo-task-proof-loop -a claude-code

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

GitHub CLI
$ gh skill install DenisSergeevitch/repo-task-proof-loop repo-task-proof-loop --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
repo-task-proof-loop
GitHub stars
730
Token cost
~3.8k tokens
SKILL.md length
2,012 words
Files
40 (incl. scripts, references, assets)
Skills in repo
1
Repo updated
First seen
Licence
Apache-2.0

At a glance

Repo-local workflow skill for large coding tasks. An agent skill from DenisSergeevitch/repo-task-proof-loop.

  • Works in 5 steps: Initializes a strict repo-local task… → Seeds or updates the required artifact… → Installs project-scoped Codex and Claude… → …
  • Tasks that involve Subagents
  • SKILL.md covers What this skill does, Commands this skill supports, Initialization step and Heavy-task default workflow, plus 6 more sections
  • Tasks that involve Agent instruction files

What it does

Repo Task Proof Loop is an agent skill from DenisSergeevitch/repo-task-proof-loop. Repo-local workflow skill for large coding tasks. Initializes .agent/tasks/TASKID artifacts, installs project-scoped Codex and Claude subagents, updates AGENTS.md plus the repo's Claude guide file with the workflow, and runs a spec-freeze → build → evidence → verify → fix loop with fresh-session verification.

Its SKILL.md is about 3.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 45 other files, including scripts, reference files and assets (for example `AGENTS.md`, `CLAUDE.md` and `README.md`). Compatibility notes: Skills-compatible coding agents. Integrates with Codex and Claude Code project-scoped subagents. Bundled scripts require Python 3.10+.

It sits in Agent Workflows, covering Subagents and Agent instruction files. The repository describes itself as: Spec driven skill with subagents spawning. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Subagents
  • Tasks that involve Agent instruction files

Example prompts

  • “/repo-task-proof-loop”

Requirements

  • Python 3
  • Compatibility (from SKILL.md): Skills-compatible coding agents. Integrates with Codex and Claude Code project-scoped subagents. Bundled scripts require Python 3.10+.

Workflow steps

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

  1. Initializes a strict repo-local task folder under .agent/tasks//
  2. Seeds or updates the required artifact files
  3. Installs project-scoped Codex and Claude subagent templates into .codex/agents/ and .claude/agents/
  4. Updates the repo-root AGENTS.md Codex baseline plus the repo's Claude guide file (CLAUDE.md or .claude/CLAUDE.md) with a managed block…
  5. Guides the agent through a strict loop

What it can do on your machine

Read from SKILL.md and the folder at commit 8536221. 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/, which the agent can run.

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

  • Network

    No URLs in SKILL.md.

    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.

  • Compatibility

    Skills-compatible coding agents. Integrates with Codex and Claude Code project-scoped subagents. Bundled scripts require Python 3.10+.

    From compatibility in the SKILL.md frontmatter.

Context cost

Repo Task Proof Loop loads about 3.8k tokens when it runs, and up to ~13k if it reads all its reference files. Until then it costs about 83 tokens; SKILL.md has 2,012 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~83
When it runs · the whole SKILL.md, loaded when a task matches
~3.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~13k

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 passed

The automated check found no risky patterns in SKILL.md.

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 DenisSergeevitch/repo-task-proof-loop at commit 8536221, republished under its Apache-2.0 licence (© DenisSergeevitch). 2,012 words, ~3,767 tokens.

Download SKILL.mdSave it as .claude/skills/repo-task-proof-loop/SKILL.md (or your agent's skills folder). This skill also uses 39 other files; get the full folder from GitHub.
name
repo-task-proof-loop
description
Repo-local workflow skill for large coding tasks. Initializes .agent/tasks/TASK_ID artifacts, installs project-scoped Codex and Claude subagents, updates AGENTS.md plus the repo's Claude guide file with the workflow, and runs a spec-freeze → build → evidence → verify → fix loop with fresh-session verification.
compatibility
Skills-compatible coding agents. Integrates with Codex and Claude Code project-scoped subagents. Bundled scripts require Python 3.10+.
license
Apache-2.0
metadata.author
OpenAI
metadata.version
1.0.0

Repo Task Proof Loop

Use this skill when the user wants a repeatable, auditable implementation workflow for a non-trivial coding task, especially a feature, refactor, migration, or bug fix that should leave repo-local proof in .agent/tasks/<TASK_ID>/.

All task artifacts created by this workflow must stay inside the repository.

When the examples below mention scripts/task_loop.py, that path is relative to this skill root. Run it while your shell working directory is inside the target repository.

What this skill does

  1. Initializes a strict repo-local task folder under .agent/tasks/<TASK_ID>/
  2. Seeds or updates the required artifact files
  3. Installs project-scoped Codex and Claude subagent templates into .codex/agents/ and .claude/agents/
  4. Updates the repo-root AGENTS.md Codex baseline plus the repo's Claude guide file (CLAUDE.md or .claude/CLAUDE.md) with a managed block that explains the workflow
  5. Guides the agent through a strict loop:
    • spec freeze
    • builder implementation
    • evidence packing
    • fresh verification
    • minimal fix
    • fresh verification again until PASS

See:

  • references/REFERENCE.md
  • references/COMMANDS.md
  • references/SUBAGENTS.md
  • references/SCHEMAS.md

Commands this skill supports

Treat the following words as commands when the user invokes this skill:

  • init <TASK_ID>: create .agent/tasks/<TASK_ID>/, install or refresh subagent templates, and update AGENTS.md plus the repo's Claude guide file
  • freeze <TASK_ID>: create or refine spec.md from the user task, task file, and repo guidance
  • build <TASK_ID>: implement the task against the frozen spec
  • evidence <TASK_ID>: create or refresh evidence.md, evidence.json, and raw artifacts without changing production code
  • verify <TASK_ID>: run a fresh verifier pass and write verdict.json, plus problems.md when needed
  • fix <TASK_ID>: apply the smallest safe fix set from problems.md, then refresh the evidence bundle
  • run <TASK_ID>: execute the full loop from spec freeze through verification
  • status <TASK_ID>: summarize current artifact status

If the user does not supply a command, infer the next step from repo state:

  • If the task folder does not exist, run init first. If the user clearly wants initialization only, stop there. Otherwise, after init succeeds and .agent/tasks/<TASK_ID>/spec.md exists, continue by re-evaluating repo state in the same turn. Do not overlap init with freeze, build, evidence, verify, fix, validate, status, or subagent work.
  • If spec.md is missing or placeholder-only, do freeze
  • If implementation is not yet complete, do build
  • If evidence is stale or missing, do evidence
  • If no fresh verdict exists, do verify
  • If verdict is not PASS, do fix

Initialization step

Run the bundled initializer from the repository root or current working directory inside the repo:

bash
scripts/task_loop.py init --task-id <TASK_ID>

Optional task seeding:

bash
scripts/task_loop.py init --task-id <TASK_ID> --task-file path/to/task.md
scripts/task_loop.py init --task-id <TASK_ID> --task-text "User task text"

The initializer will:

  • resolve the repo root
  • create .agent/tasks/<TASK_ID>/
  • create all required artifacts, including placeholders under raw/
  • install project-scoped subagent files
  • insert or refresh managed workflow blocks in AGENTS.md and the repo's Claude guide file

For Codex, the initializer keeps its managed workflow block in the repo-root AGENTS.md. Codex also supports AGENTS.override.md and configured fallback guide filenames; nested files closer to the code still take precedence, and this skill intentionally does not overwrite them. If init creates or rewrites AGENTS.md during a running Codex session, start a new Codex session before relying on the updated instructions. Codex snapshots project-doc guidance at session start.

For Claude Code, the initializer keeps its managed workflow block in the repo-root CLAUDE.md. Claude Code also supports .claude/CLAUDE.md, .claude/rules/*.md, and CLAUDE.local.md, but this skill treats root CLAUDE.md as the primary project guide because Claude surfaces it directly.

In Claude Code, if init just wrote or refreshed .claude/agents/* during the current session, do not assume those updated agents are already available mid-session.

Treat init as a serial prerequisite. Never overlap it with freeze, build, evidence, verify, fix, validate, status, or child-agent spawning.

Heavy-task default workflow

For large tasks, keep the user-facing request simple. In Codex, continue serially unless the user explicitly asks for delegation or parallel agent work; after that authorization, the skill can choose the internal child setup automatically when the current product surface supports delegation and the task shape warrants it.

Preferred delegated sequence
  1. Run init <TASK_ID> if needed. Wait for it to finish, then confirm .agent/tasks/<TASK_ID>/spec.md and the repo-local task structure exist before continuing.
  2. Only after init completes, spawn exactly one spec-freezer subagent and wait for it
  3. Spawn exactly one builder subagent and let it implement
  4. Continue with the same builder session for evidence packing
  5. Spawn exactly one fresh verifier subagent and wait for it
  6. If verdict is not PASS, spawn exactly one fixer subagent
  7. Spawn one fresh verifier subagent again
  8. Repeat steps 6-7 until the verifier returns PASS or the user stops the loop
Codex adaptive fan-out

Use this only after the user has explicitly authorized Codex delegation and the task is broad enough to benefit from bounded parallel work. Use the simpler serial sequence above for narrow tasks.

Good fits:

  • multiple independent codebase questions must be answered before the spec is stable
  • implementation can be split into disjoint write scopes
  • proof requires several independent read-only checks across different surfaces

Codex pattern:

  1. init stays serial.
  2. If the task is still ambiguous, fan out up to 3 built-in explorer children in parallel. Give each one a single question, subsystem, or path scope. Wait for them, then freeze the spec.
  3. Spawn one spec-freezer child and wait for it.
  4. Spawn one task-builder child as the integration owner.
  5. If implementation splits cleanly, the parent may also spawn bounded built-in worker children in parallel. Each worker must have explicit file or module ownership and must not write evidence.md, evidence.json, verdict.json, or problems.md.
  6. Use send_input or the equivalent follow-up surface to keep the integration builder alive for evidence packing. The builder remains the single owner of the evidence bundle.
  7. If extra proof is needed, the parent may fan out a small bounded set of read-only explorer children to rerun disjoint checks or inspect separate proof gaps in parallel. Those children may report commands, outputs, and findings, but they do not write verdict.json.
  8. Run exactly one fresh verifier child for each verify pass.
Show full SKILL.md (1,033 more words)Show less
Platform behavior
  • In Codex, keep the normal path serial and auto-mode-first after init. Avoid surfacing delegation internals unless they materially affect the work.
  • In Codex, spawn bounded subagents only when the user explicitly asks for sub-agents, delegation, or parallel agent work.
  • In Codex, once delegation is authorized, the skill may choose the matching child roles and whether to stay one-child-at-a-time or use bounded fan-out. The user should not need to name specific child roles or slash commands.
  • In Codex, child spawning is still an explicit parent-orchestrator action. If the current Codex surface blocks delegation, say so briefly only when it materially affects the work, then continue serially.
  • In Codex, keep the task tree shallow. The parent session should spawn research, builder, fixer, and verifier children directly instead of asking one custom task child to orchestrate more children.
  • In Codex, once delegation is authorized, choose between one-child-at-a-time delegation and bounded fan-out from the frozen spec, repo shape, and current delegation surface. Keep init, evidence ownership, and every verifier pass serialized either way.
  • In Codex, keep helper fan-out modest and wave-based. Prefer up to 3 parallel helper children at once, wait for that wave to finish, then decide the next phase.
  • In Codex, built-in explorer is the first choice for read-only repo discovery and proof probes. Built-in worker is appropriate for bounded disjoint implementation or check reruns when you can assign explicit ownership.
  • In Codex, reuse the live builder child for evidence packing by sending it a follow-up instruction. Verifier passes must use a fresh child or fresh session; do not satisfy verifier freshness by resuming an earlier verifier. Builder and fixer children can be reused or resumed when you intentionally want that context back.
  • In Codex, inspect the current child-thread list before reusing or resuming a child. Use /agent in Codex CLI or any equivalent child-thread inventory surface available in the current Codex product surface.
  • In Codex, the plan/todo checklist UI from update_plan is optional session guidance only. It is useful for live progress display, but it is not the source of truth for this workflow.
  • In Claude Code, the skill should decide whether to stay on the main thread or let the main Claude session auto-delegate the current phase to a matching built-in or project subagent after init. The user should not need to request a specific Claude subagent or delegation mode separately.
  • In Claude Code, TodoWrite or the visible task/todo UI is optional session-scoped progress display only. It can help with live tracking in the current session, but it is not the source of truth for this workflow.
  • In Claude Code, prefer the installed project subagents from .claude/agents/, with descriptions written as proactive trigger conditions for the matching proof-loop phase. Claude's main session routes by the task request, subagent descriptions, and current context, so keep each phase prompt clear in natural language. Reuse the same builder child for the evidence step by default. Only run a fresh builder in evidence-only mode if the original builder session is unavailable or you intentionally discarded it. If init just refreshed .claude/agents/* during the current Claude session, fall back to the main thread or already-visible agents instead of assuming the refreshed ones are available immediately.
  • In Claude Code, keep the orchestration flat: main-session auto-delegation is fine, but the proof-loop workflow agents themselves are leaf roles. The parent session should own the proof-loop phase transitions instead of asking one custom task agent to spawn another.
  • In Claude Code, the canonical durable state is always the repo-local artifact set under .agent/tasks/<TASK_ID>/, especially spec.md, evidence.md, evidence.json, verdict.json, and problems.md.
  • If subagents are unavailable, preserve the same role separation across separate sessions or clear mode changes in the current session.

Use the exact role prompts from references/COMMANDS.md.

Spec freeze requirements

spec.md must contain at least:

  • original task statement
  • explicit acceptance criteria labeled AC1, AC2, ...
  • constraints
  • non-goals

It may also include:

  • repo guidance sources
  • verification plan
  • assumptions resolved narrowly from the user request

Do not edit production code during spec freeze.

Evidence packing requirements

evidence.md and evidence.json must judge each acceptance criterion independently with one of:

  • PASS
  • FAIL
  • UNKNOWN

Evidence packing may run missing checks, but it must not keep changing production code.

Every PASS must cite concrete proof such as:

  • file paths
  • commands run
  • exit codes
  • output summaries
  • artifact paths under raw/

Do not claim overall PASS in the evidence bundle unless every acceptance criterion is PASS.

Fresh verification requirements

The verifier must be a fresh session or fresh subagent. In Codex, do not satisfy this requirement by resuming a prior verifier child.

The verifier must judge the current repository state and current rerun results, not the builder narrative.

The verifier writes:

  • .agent/tasks/<TASK_ID>/verdict.json
  • .agent/tasks/<TASK_ID>/problems.md only when overall verdict is not PASS

problems.md must include, for each non-PASS criterion:

  • criterion id and text
  • status
  • why it is not proven
  • minimal reproduction steps
  • expected vs actual
  • affected files
  • smallest safe fix
  • corrective hint in 1-3 sentences

The verifier must not modify production code or backfill the evidence bundle.

Fixer requirements

The fixer reads only:

  • spec.md
  • verdict.json
  • problems.md

The fixer must:

  • reconfirm each listed problem in the codebase before editing
  • make the smallest safe change set
  • avoid regressing already-passing criteria
  • regenerate evidence.md, evidence.json, and raw artifacts
  • stop without writing final sign-off

Validation

Before claiming the workflow is correctly initialized or the artifact set is complete, run:

bash
scripts/task_loop.py validate --task-id <TASK_ID>

Run validate only after init has fully finished. If it reports initialization in progress, wait and rerun it instead of treating that result as stable task failure.

For a quick summary:

bash
scripts/task_loop.py status --task-id <TASK_ID>

Run status only after init has fully finished when you need stable task state. If it reports init_in_progress: true, treat that as a retry-later condition.

Guardrails

  • Keep .agent/tasks/<TASK_ID>/ inside the repo
  • Treat the Codex todo/checklist UI as ephemeral progress only; the durable workflow state lives in .agent/tasks/<TASK_ID>/
  • Never claim task completion unless every acceptance criterion is PASS
  • Separate evaluator and fixer roles
  • Keep Codex fan-out shallow and bounded. Parallel helpers may inform the proof loop, but one builder still owns evidence and one fresh verifier still owns verdict.
  • Keep the verifier fresh
  • Prefer the smallest defensible diffs during fixes
  • Preserve existing user guidance outside the managed blocks in AGENTS.md and the repo's chosen Claude guide file

© DenisSergeevitch, Apache-2.0. 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 39 other files (scripts, references, assets) in the repository root of DenisSergeevitch/repo-task-proof-loop.

  • SKILL.md
  • .gitignore
  • AGENTS.md
  • CLAUDE.md
  • LICENSE
  • README.md
  • VERIFICATION.md
  • agents/openai.yaml
  • assets/images/banner.png
  • assets/images/proof-loop-diagram.png
  • assets/schemas/evidence.schema.json
  • assets/schemas/verdict.schema.json
  • assets/templates/claude/task-builder.md.tmpl
  • assets/templates/claude/task-fixer.md.tmpl
  • assets/templates/claude/task-spec-freezer.md.tmpl
  • … and 25 more

Open the folder on GitHubat commit 8536221

Compare with similar skills

Repo Task Proof Loop 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.

Repo Task Proof Loop compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Repo Task Proof Loop this skillDenisSergeevitch/repo-task-proof-loop730—~3.8kAutomated safety check: PassApache-2.0
Task Observerrebelytics/one-skill-to-rule-them-all3.2k1 repos~12kAutomated safety check: PassCC-BY-4.0
Harness Agent Team Designerrevfactory/harness9.1k—~4.5kAutomated safety check: PassApache-2.0
Rules Distillationaffaan-m/ECC276k2 repos~2.3kAutomated safety check: PassMIT
Claude Docs Consultantcentminmod/my-claude-code-setup2.7k—~959Automated safety check: PassMIT
Creating Claude Code Agentspr-pm/prpm1222 repos~4kAutomated safety check: PassMIT

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Categories

Questions about Repo Task Proof Loop

What does Repo Task Proof Loop do?

Repo-local workflow skill for large coding tasks. An agent skill from DenisSergeevitch/repo-task-proof-loop. Repo Task Proof Loop is an agent skill from DenisSergeevitch/repo-task-proof-loop. Repo-local workflow skill for large coding tasks.

When should I use Repo Task Proof Loop?

Repo Task Proof Loop fits situations like: tasks that involve Subagents; tasks that involve Agent instruction files.

How do I install Repo Task Proof Loop in Claude Code?

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

How do I install Repo Task Proof Loop in Codex?

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

Can I use Repo Task Proof Loop 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 DenisSergeevitch/repo-task-proof-loop --skill repo-task-proof-loop -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/repo-task-proof-loop, .gemini/skills/repo-task-proof-loop, .github/skills/repo-task-proof-loop and .opencode/skills/repo-task-proof-loop in your project.

What does Repo Task Proof Loop need to run?

SKILL.md names no scripts, command-line tools or credentials: Repo Task Proof Loop is instructions for the agent only. Our summary lists: Python 3. Compatibility (from SKILL.md): Skills-compatible coding agents. Integrates with Codex and Claude Code project-scoped subagents. Bundled scripts require Python 3.10+..

Does Repo Task Proof Loop access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Repo Task Proof Loop safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Repo Task Proof Loop use?

Repo Task Proof Loop is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Repo Task Proof Loop use?

About 3.8k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 9k tokens, read only when the agent opens those files.

What are the alternatives to Repo Task Proof Loop?

Skills that share tags, products or a category with Repo Task Proof Loop: Task Observer (rebelytics/one-skill-to-rule-them-all, 3.2k stars), Harness Agent Team Designer (revfactory/harness, 9.1k stars), Rules Distillation (affaan-m/ECC, 276k stars) and Claude Docs Consultant (centminmod/my-claude-code-setup, 2.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Repo Task Proof Loop?

DenisSergeevitch (a GitHub user) maintains it in DenisSergeevitch/repo-task-proof-loop, which has 730 GitHub stars. The repository was last updated on April 1, 2026.

Source: DenisSergeevitch/repo-task-proof-loop on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.