Wiki Ingest
paperclipai/paperclip
A skill your agent uses when an operation issue asks to ingest a captured raw/ source into the LLM Wiki, or the user says "ingest <slug".
Full execution protocol for MODE: PLAN -- plan creation, external plan ingestion, QA gate persistence, task granularity, and traceability checks.
$ npx skills add ZaxbyHub/opencode-swarm --skill swarm-plan -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ZaxbyHub/opencode-swarm swarm-plan --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/ZaxbyHub/opencode-swarm.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/swarm-plan .claude/skills/swarm-plan && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "swarm-plan" agent skill from https://github.com/ZaxbyHub/opencode-swarm/tree/main/.claude/skills/swarm-plan into .claude/skills/swarm-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "swarm-plan", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/ZaxbyHub/opencode-swarm/tree/main/.claude/skills/swarm-planType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add ZaxbyHub/opencode-swarm --skill swarm-plan -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ZaxbyHub/opencode-swarm swarm-plan --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ZaxbyHub/opencode-swarm.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/swarm-plan .agents/skills/swarm-plan && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "swarm-plan" agent skill from https://github.com/ZaxbyHub/opencode-swarm/tree/main/.claude/skills/swarm-plan into .agents/skills/swarm-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "swarm-plan", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ZaxbyHub/opencode-swarm --skill swarm-plan -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ZaxbyHub/opencode-swarm swarm-plan --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ZaxbyHub/opencode-swarm.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/swarm-plan .cursor/skills/swarm-plan && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "swarm-plan" agent skill from https://github.com/ZaxbyHub/opencode-swarm/tree/main/.claude/skills/swarm-plan into .cursor/skills/swarm-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "swarm-plan", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/ZaxbyHub/opencode-swarm.git --path .claude/skills/swarm-plan--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add ZaxbyHub/opencode-swarm --skill swarm-plan -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ZaxbyHub/opencode-swarm swarm-plan --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ZaxbyHub/opencode-swarm.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/swarm-plan .gemini/skills/swarm-plan && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "swarm-plan" agent skill from https://github.com/ZaxbyHub/opencode-swarm/tree/main/.claude/skills/swarm-plan into .gemini/skills/swarm-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "swarm-plan", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install ZaxbyHub/opencode-swarm swarm-planInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add ZaxbyHub/opencode-swarm --skill swarm-plan -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ZaxbyHub/opencode-swarm.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/swarm-plan .github/skills/swarm-plan && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "swarm-plan" agent skill from https://github.com/ZaxbyHub/opencode-swarm/tree/main/.claude/skills/swarm-plan into .github/skills/swarm-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "swarm-plan", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ZaxbyHub/opencode-swarm --skill swarm-plan -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ZaxbyHub/opencode-swarm swarm-plan --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ZaxbyHub/opencode-swarm.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/swarm-plan .opencode/skills/swarm-plan && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "swarm-plan" agent skill from https://github.com/ZaxbyHub/opencode-swarm/tree/main/.claude/skills/swarm-plan into .opencode/skills/swarm-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "swarm-plan", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
swarm-planFull execution protocol for MODE: PLAN -- plan creation, external plan ingestion, QA gate persistence, task granularity, and traceability checks.
Swarm Plan is an agent skill from ZaxbyHub/opencode-swarm. Full execution protocol for MODE: PLAN -- plan creation, external plan ingestion, QA gate persistence, task granularity, and traceability checks.
Its SKILL.md is about 7.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: Architect-centric agentic swarm plugin for OpenCode. Hub-and-spoke orchestration with SME consultation, code generation, and QA review. The licence is MIT.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit b63a4bd. It shows what the files ask for, not the result of running them.
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.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Swarm Plan loads about 7.5k tokens when it runs. Until then it costs about 39 tokens; SKILL.md has 4,040 words of instructions outside code blocks.
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.
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); files beside SKILL.md are not scanned.
The full file from ZaxbyHub/opencode-swarm at commit b63a4bd, republished under its MIT licence (© ZaxbyHub). 4,040 words, ~7,461 tokens.
.claude/skills/swarm-plan/SKILL.md (or your agent's skills folder).This protocol is loaded on demand by the architect runtime. The architect prompt keeps only activation, action, and hard safety constraints; the full execution details live here.
Before planning, call repo_map with graph_health, then package_boundaries and key_files, followed by a targeted source-bearing context_pack; a preflight_packet (bounded ontology of roles, routes, data, and security findings) frames planning risk, and per-file ontology facts sharpen it. Graph evidence is advisory only. If freshness is stale or inconclusive, confidence is low, source is missing, the language is unsupported/dynamic, the graph is absent, or an action fails, inspect the direct source and searches before committing the plan.
PLANNING PROFILE (authoritative): obey the runtime-injected [PLANNING PROFILE — AUTHORITATIVE] directive, which is produced by the same resolver used by
save_plan. Select exactly one path:
balanced: use durable QA/execution defaults and do not pause for the full
questionnaire, spec ceremony, or complete clarification funnel. Ask only for
unresolved material ambiguity, destructive/high-risk authorization, or a
decision only the user can make. save_plan exact-binds the default QA
profile. Persist planning_profile: "balanced".strict (including locked legacy profiles with no stored field): require an
effective spec, run the complete clarification funnel, present the unified
QA/execution questionnaire, and wait for the user's answers before saving.
Persist planning_profile: "strict" only when the field is already explicit
or this is a new/unlocked plan; do not materialize it into a locked legacy
profile.A locked profile may ratchet balanced to strict; it never moves strict to
balanced.
SPEC POLICY (profile-dependent — check before planning):
An effective spec exists iff /swarm sdd status reports a resolved spec (it reflects readEffectiveSpecSync, which returns null for no sources, multiple competing sources, multi-feature Spec-Kit without a selected feature, or any unresolvable state). Do NOT enumerate these cases — defer to /swarm sdd status.
/swarm sdd status):strict: stop and enter MODE: SPECIFY (or materialize a selected SDD source
with explicit consent). Strict planning cannot save without an effective
spec.balanced: a spec is optional. Offer the choices below only when a spec
would materially resolve ambiguity; otherwise proceed directly.balanced.balanced, this is a SOFT gate — option 2 lets the user proceed without a spec./swarm sdd status) and compare its first heading (or feature description) against the current planning context (the user's request and any existing plan.md title/phase names)strict, offer options 1 and 2 only. In balanced, offer all three options:balanced only) → proceed to planning below ignoring the existing specbalanced user chose option 3 above, proceed without spec: skip all spec-based steps and proceed directly to planningThis is a soft gate only in balanced. In strict, a missing effective spec is
a hard prerequisite and save_plan will return SPEC_REQUIRED.
STRICT-ONLY SAVE_PLAN SPEC_REQUIRED RECOVERY:
When save_plan returns a SPEC_REQUIRED rejection (no effective spec found), the architect MUST:
/swarm sdd status to determine why no effective spec resolved./swarm sdd status shows NO sources → transition to MODE: SPECIFY./swarm sdd status shows multiple competing sources (e.g., openspec AND specify with no native) → ask the user which provider to use (openspec or speckit), then run /swarm sdd project --source <user_choice> (obtain explicit consent first; add --overwrite only if a native .swarm/spec.md already exists). Then re-attempt save_plan./swarm sdd status shows Spec-Kit with multiple features → ask the user which feature, then run /swarm sdd project --source speckit --feature <id> (obtain explicit consent first; add --overwrite only if a native .swarm/spec.md already exists). Then re-attempt save_plan./swarm sdd status shows a single resolvable source but it was not yet materialized: run /swarm sdd project (obtain explicit consent first; add --overwrite only if a native .swarm/spec.md already exists). Then re-attempt save_plan.Run CODEBASE REALITY CHECK scoped to codebase elements referenced in the effective spec or user constraints. Discrepancies must be reflected in the generated plan.
In strict, before drafting or saving the plan, the architect MUST offer General Council advisory input when council.general.enabled is true in the resolved opencode-swarm config and a search API key is configured. In balanced, offer it only when current external facts could materially change the plan; do not introduce a pause merely because the feature is configured.
web_search queries grounded in the work being planned.the active swarm's council_generalist agent, the active swarm's council_skeptic agent, and the active swarm's council_domain_expert agent in PARALLEL with the RESEARCH CONTEXT.convene_general_council with mode general.save_plan.save_plan.save_plan rather than writing an ungrounded plan.General Council is advisory and distinct from council_mode, phase_council, and final_council. It is not a QA gate. Its purpose here is to make current external context available before the architect writes any plan and before any critic pre-plan review.
In strict, before calling save_plan — whether creating a new plan or finalizing an external plan ingestion — the architect MUST run this four-stage clarification funnel. In balanced, use the same classification concepts internally but surface only unresolved material ambiguity, destructive/high-risk authorization, or decisions only the user can make; do not run the full funnel as ceremony.
Identify ALL uncertainties that could affect the plan. There is NO hard cap on the internal inventory. Cover at minimum:
Classify each item as exactly one of:
self_resolved: answered from the user request, spec, plan, codebase reality check, .swarm/context.md, repo conventions, or an informed default. If the default is not directly supported by user request, spec, or recorded context, classify as user_decision rather than self_resolved.critic_resolved: sent to Critic Sounding Board and resolved by the critic.research_needed: needs SME/explorer/domain lookup before user escalation. Important: If research is ongoing, apply a fixed 5-minute protocol budget to research_needed. If research does not complete before the budget expires, automatically reclassify the item to user_decision with a note that research was incomplete, then surface it to the user. This prevents the clarification funnel from stalling while waiting for external research.user_decision: only the user can decide because it affects product scope, risk tolerance, policy, budget, UX, rollout, or destructive behavior.deferred_nonblocking: useful follow-up detail that does not block a correct initial plan and can be explicitly recorded as an assumption or follow-up.Before asking the user any planning clarification question, the architect MUST consult critic_sounding_board with the candidate question set and context.
For each item classified as research_needed or user_decision in Stage 2, send it to the critic. The critic responds with a verdict from the SoundingBoardVerdict enum (UNNECESSARY | RESOLVE | REPHRASE | APPROVED). The mapping between critic verdicts and funnel actions is:
| Critic Verdict (SoundingBoardVerdict) | Funnel Action | Meaning |
|---|---|---|
UNNECESSARY | DROP | Item is unnecessary or answerable from existing context |
RESOLVE | RESOLVE | Critic supplies the answer or recommended default |
REPHRASE | REPHRASE | Question is valid but should be clearer, narrower, or grouped |
APPROVED | ASK_USER | User decision is genuinely required |
Hard constraint: Items in the Always-Surface Categories list (below) MUST NOT receive UNNECESSARY/DROP from the critic — only REPHRASE or APPROVED/ASK_USER are allowed. If the critic attempts to UNNECESSARY/DROP an always-surface item, override to APPROVED/ASK_USER.
This always-surface protection remains mandatory in every planning profile.
Overconfidence guard: If the critic attempts to self-resolve an item by supplying an answer (verdict RESOLVE) but the underlying default is not directly supported by user request, spec, or recorded context, the architect MUST classify the item as user_decision rather than self_resolved. Unsupported defaults must not be silently accepted.
Update classifications based on critic response:
UNNECESSARY/DROP → reclassify as self_resolved and record the reason.RESOLVE → reclassify as critic_resolved and record the answer as an assumption.REPHRASE → update the question wording and keep as candidate.APPROVED/ASK_USER → confirm as user_decision.The architect MUST update the plan's assumptions with all resolved items before proceeding to Stage 4.
Strict-only exception: QA gate selection questions are direct user decisions and do NOT need to go through the funnel. Balanced uses the durable default profile and does not present this dialogue.
If any items remain classified as user_decision after Stage 3, present them as a structured decision packet — NOT as an arbitrary subset or a single question.
The packet MUST include for each decision:
The architect MAY ask questions one at a time in interactive mode, but MUST preserve and report the full unresolved list. The architect MUST NOT drop unresolved decisions because of a session question cap.
The critic may improve wording or confirm prior context, but these categories MUST be surfaced to the user unless already explicitly answered by the user or by recorded context:
All items resolved in Stages 2-3 (self_resolved, critic_resolved, deferred_nonblocking) MUST be recorded as explicit assumptions in the relevant plan task descriptions or acceptance criteria passed to save_plan. Silently dropping resolved uncertainties is a protocol violation — every uncertainty that entered the funnel must have a recorded outcome.
The plan generated by save_plan MUST include explicit assumptions and remaining unresolved decisions in the task descriptions or acceptance criteria — not silently omit them.
Implementation Note: The hard constraint against DROP on always-surface items (Stage 3 of the clarification funnel) is currently enforced via skill instructions to the architect. A lightweight runtime enforcement mechanism is recommended: when the critic sounding board verdict response is parsed, validate that any items tagged as "always-surface" do not receive UNNECESSARY/DROP verdicts. If a DROP verdict is encountered on an always-surface item, override it to APPROVED/ASK_USER at the code level rather than relying solely on prompt-based enforcement.
This mechanical enforcement prevents the following failure mode: the architect prompt instructs the override, but due to parsing errors, context limits, or model behavior variance, the DROP verdict is mistakenly applied to an always-surface item and silently accepted. The validation should occur in the decision-packet assembly code (when building the final clarification packet to surface to the user) and should emit a warning log when an override is applied. This is tracked as future work in a follow-up issue; until then, enforcement relies on the skill instructions.
Draft the complete implementation plan in memory first. Required parameters:
title: The real project name from the spec (NOT a placeholder like [Project])swarm_id: The swarm identifier (e.g. "mega", "local", "paid")phases: Array of phases, each with id (number), name (string), and tasks (array)id (e.g. "1.1"), description (real content from spec — bracket placeholders like [task] will be REJECTED)size (small/medium/large), depends (array of task IDs), acceptance (string)QA AND EXECUTION PROFILE BOOTSTRAP (before first save_plan).
files_touched scopes. Freeze the exact raw plan identity as swarm_id plus plan_title (the same title passed to save_plan). Do not normalize, shorten, or rename either value between profile creation and plan save. An intentional identity replacement must use confirm_identity_change: true; never silently create a second profile because wording changed.strict: present the following unified four-choice dialogue in one message and wait for one complete answer. Silence is not consent. balanced: skip this dialogue and continue with the durable defaults.<!-- BEGIN QA_GATE_BODY -->
Present the eleven gates with their defaults (DEFAULT_QA_GATES), parallel coder count, commit frequency, and auto_proceed as a single user-facing section. Offer the user a one-shot choice: accept defaults, or customize. The eleven gates are:
CouncilMemberVerdict objects, and calls write_final_council_evidence. This does not require council.general.enabled.Additionally, present these three sub-items as part of the same exchange:
COMMON MISCONCEPTION: worktree isolation is baseline for standard parallel coders, governed by the parallel execution profile plus top-level
worktree.policy. It is not provided by Lean Turbo or Epic. Do not recommend Lean Turbo or Epic to obtain worktree isolation; recommend them only for what they add beyond baseline (Lean Turbo: lane planning, file locks, phase reviewer, integrated diff; Epic: co-change awareness and auto-decide). Worktrees also do not make overlapping scopes safe: dependency readiness, file-disjoint scopes, and merge-back ownership are still required.
<!-- END QA_GATE_BODY -->
autonomy=auto, do not pause. Use the loop skill's balanced-speed defaults: reviewer, test_engineer, sme_enabled, critic_pre_plan, sast_enabled, and drift_check ON; council_mode, hallucination_guard, mutation_test, phase_council, and final_council OFF. Choose the largest safe parallel count from the drafted scopes (1 when overlap or uncertainty exists), keep phase-level commits (commit_after_each_completed_task: false), and set auto_proceed: true.strict: before the first save_plan, persist all eleven gate booleans with set_qa_gates({ swarm_id: <exact swarm_id>, plan_title: <exact title>, ...gates }). If it fails, stop and resolve the profile error. balanced: do not call set_qa_gates merely to reproduce defaults; save_plan creates and exact-binds them.
Recovery for upgraded legacy plans: if get_qa_gate_profile, save_plan, or an execution gate reports that the QA profile is not exact-bound, run set_qa_gates({ swarm_id: <exact swarm_id>, plan_title: <exact title>, adopt_legacy_binding_only: true }). This exact-binds the existing profile without changing gates or its lock, then you retry the blocked read/save/enforcement step.save_plan with the same exact identity, the full drafted phases, and the complete locked profile:save_plan({
title: <exact plan_title>,
swarm_id: <exact swarm_id>,
phases: [...],
execution_profile: {
parallelization_enabled: <parallel coders > 1>,
max_concurrent_tasks: <selected count>,
council_parallel: false,
locked: true,
auto_proceed: <selected boolean>,
commit_after_each_completed_task: <selected boolean>
}
})get_qa_gate_profile({ swarm_id: <exact swarm_id>, plan_title: <exact plan_title> }). Use its persisted critic_pre_plan value for the critic decision; do not rely on a default, conversation memory, or transient context. Any retry must reuse the frozen identity and the full execution profile.The locked execution profile is plan-scoped and authoritative. Do not change it after tasks start. A global concurrency setting cannot override it.
If the authoritative ledger-backed save_plan tool is unavailable, STOP and report the blocker. Never ask a coder to hand-write .swarm/plan.md or any other derived plan projection.
TASK GRANULARITY RULES:
TEST TASK DEDUPLICATION: The QA gate (Stage B, step 5l) runs test_engineer-verification on EVERY implementation task. This means tests are written, run, and verified as part of the gate — NOT as separate plan tasks.
DO NOT create separate "write tests for X" or "add test coverage for X" tasks. They are redundant with the gate and waste execution budget.
Research and in-repo experience show that large shifts in test-writing volume yield little resolution change while consuming substantially more tokens. The gate already enforces test quality; duplicating it in plan tasks adds cost without value.
CREATE a dedicated test task ONLY when:
If in doubt, do NOT create a test task. The gate handles it. Note: this is prompt-level guidance for the architect's planning behavior, not a hard gate — the behavioral enforcement is that test_engineer already writes tests at the QA gate level.
PHASE COUNT GUIDANCE:
Do not create or hand-edit .swarm/context.md as part of PLAN. Durable plan and execution policy must flow through the authoritative tools above.
TRACEABILITY CHECK (run after plan is written, when an effective spec exists):
OBLIGATION TRACEABILITY — STRUCTURAL COMPLETENESS PRECONDITION The obligation-traceability mapping is a STRUCTURAL COMPLETENESS precondition. It MUST be evaluated BEFORE the critic begins its substantive 5-axis/7-dimension rubric. An unmapped MUST/SHALL obligation makes the plan structurally incomplete — it is not an afterthought.
FR-### MAPPING (existing requirement):
/swarm sdd status) MUST map to at least one task → unmapped FRs = coverage gap, flag to userSC-### MAPPING (MUST/SHALL obligations):
/swarm sdd status) for every SC-### line whose obligation text contains MUST or SHALL/SHALL NOTREPORT FORMAT:
"TRACEABILITY: <N> FRs mapped, <M> unmapped FRs (gap), <K> tasks with no FR mapping (gold-plating risk), <P> MUST/SHALL SCs mapped, <Q> unmapped MUST/SHALL SCs (structural gap)"
After the QA gate selection and execution profile are persisted and the TRACEABILITY CHECK is complete:
get_qa_gate_profile has critic_pre_plan: true, the plan MUST be reviewed by the critic before any implementation begins. If false, skip only this critic gate.© ZaxbyHub, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .claude/skills/swarm-plan of ZaxbyHub/opencode-swarm.
Open the folder on GitHubat commit b63a4bd
Swarm Plan 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Swarm Plan this skillZaxbyHub/opencode-swarm | 494 | — | ~7.5k | Automated safety check: Pass | MIT | |
| Wiki Ingestpaperclipai/paperclip | 100k | — | ~933 | Automated safety check: Pass | MIT | |
| Agent Swarmruvnet/ruflo | 74k | 2 repos | ~891 | Automated safety check: Pass | MIT | |
| Remotion Video Creationaffaan-m/ECC | 277k | 2 repos | ~910 | Automated safety check: Pass | MIT | |
| Swarm Initruvnet/ruflo | 74k | — | ~319 | Automated safety check: Pass | MIT | |
| Agent Release Swarmruvnet/ruflo | 74k | 2 repos | ~3.5k | Automated safety check: Pass | MIT |
paperclipai/paperclip
A skill your agent uses when an operation issue asks to ingest a captured raw/ source into the LLM Wiki, or the user says "ingest <slug".
ruvnet/ruflo
Agent skill for swarm - invoke with $agent-swarm. An agent skill from ruvnet/ruflo.
affaan-m/ECC
Best practices for Remotion - Video creation in React. An agent skill from affaan-m/ECC.
ruvnet/ruflo
Initialize a multi-agent swarm with anti-drift configuration.
ruvnet/ruflo
Agent skill for release-swarm - invoke with $agent-release-swarm
ruvnet/ruflo
Agent skill for swarm-issue - invoke with $agent-swarm-issue
ZaxbyHub/opencode-swarm
Runs an evidence-gated, quote-grounded audit of a codebase for security, QA, accessibility, performance and more, and writes a verified report without changing source files.
ZaxbyHub/opencode-swarm
Drives a bug report from validation and root-cause tracing through a critic-reviewed plan, an approved minimal fix and a PR-ready closure, never merging without recorded human approval.
ZaxbyHub/opencode-swarm
Codex adapter for opencode-swarm that governs commits, pushes, draft PRs, PR body updates and CI closeout, deferring to the repo's canonical commit-pr protocol.
ZaxbyHub/opencode-swarm
Keeps plans, decisions, evidence and reviewer verdicts in small files so long multi-phase tasks survive context compaction and session resumes.
ZaxbyHub/opencode-swarm
Ingests existing pull request feedback such as review comments and CI failures, verifies each claim, fixes confirmed issues and reports closure status for every item.
ZaxbyHub/opencode-swarm
Monitor a pull request after creation and act autonomously on pushed PR activity.
Full execution protocol for MODE: PLAN -- plan creation, external plan ingestion, QA gate persistence, task granularity, and traceability checks. Swarm Plan is an agent skill from ZaxbyHub/opencode-swarm. Full execution protocol for MODE: PLAN -- plan creation, external plan ingestion, QA gate persistence, task granularity, and traceability checks.
Run `npx skills add ZaxbyHub/opencode-swarm --skill swarm-plan -a claude-code`. Or copy the skill folder (.claude/skills/swarm-plan in ZaxbyHub/opencode-swarm) into .claude/skills/swarm-plan in your project. Claude Code loads it when a task matches its description.
Run `npx skills add ZaxbyHub/opencode-swarm --skill swarm-plan -a codex`. Or copy the skill folder (.claude/skills/swarm-plan in ZaxbyHub/opencode-swarm) into .agents/skills/swarm-plan in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ZaxbyHub/opencode-swarm --skill swarm-plan -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/swarm-plan, .gemini/skills/swarm-plan, .github/skills/swarm-plan and .opencode/skills/swarm-plan in your project.
SKILL.md names no scripts, command-line tools or credentials: Swarm Plan is instructions for the agent only.
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.
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. Review the folder before installing.
Swarm Plan is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 7.5k tokens (SKILL.md is roughly 30k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Swarm Plan: Wiki Ingest (paperclipai/paperclip, 100k stars), Agent Swarm (ruvnet/ruflo, 74k stars), Remotion Video Creation (affaan-m/ECC, 277k stars) and Swarm Init (ruvnet/ruflo, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
ZaxbyHub (a GitHub organization) maintains it in ZaxbyHub/opencode-swarm, which has 494 GitHub stars. The repository holds 91 skills in this directory. The repository was last updated on October 10, 2026.
Source: ZaxbyHub/opencode-swarm on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.