swarm-debug
Systematic debugging — evidence before hypotheses, hypotheses before fixes, root cause before patches, and the diagnosis saved to the vault. Use for any real…
Milestone review sweep — a strong model audits everything since the last sweep against the spec: requirement fulfillment, standards, simplification, risk. Use when a milestone's tickets are done, before opening the next milestone, or when asked to review/audit/validate completed
$ npx -y skills add AnmarHani/SwarmVault --skill swarm-review --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/swarm-reviewContext preview
The summary Claude sees to decide when to auto-load this skill.
Milestone review sweep — a strong model audits everything since the last sweep against the spec: requirement fulfillment, standards, simplification, risk. Use when a milestone's tickets are done, before opening the next milestone, or when asked to review/audit/validate completed
name: swarm-review description: Milestone review sweep — a strong model audits everything since the last sweep against the spec: requirement fulfillment, standards, simplification, risk. Use when a milestone's tickets are done, before opening the next milestone, or when asked to review/audit/validate completed work.
Reviews against the **spec**, not just the code — that is the difference between this and a linter. Expect a top-tier model; warn if the session runs less. Milestone cadence only (token economy): not per-commit.
**Scope:** the milestone's diff (git log since last sweep), its tickets, and its FR specs.
1. **Fulfillment** (the one that matters most): every Must-FR of the milestone, individually — no sampling. Are the acceptance criteria actually met? Do the tests *assert the criteria* (not just execute the code)? Is the FR → ticket → commit → test chain intact? 2. **Standards:** naming, error handling (exceptions handled, not swallowed), comment discipline (light, constraint-stating), test quality (behavior asserted, not implementation), commit hygiene — audited against swarm-implement's `references/clean-code.md` where available, **including its dogma traps**: fragment soup, one-implementation abstractions, pattern theater, and SRP shrapnel are findings, not compliance. **End-user text** shipped in the milestone (UI strings, README, release notes, marketing) is audited against the project's `voice.md` and the audience firewall — load swarm-write for the criteria. 3. **Simplification:** duplicated logic to merge, needless abstraction to delete, blocks that could be simpler or generalized. If a fix is obvious and small, still ticket it — see the rule below. 4. **Risk:** input validation gaps, security smells, and a devil's-advocate pass — "what assumption, if wrong, hurts most?"
One per issue, compact (machine lane): severity (`blocker/major/minor`), FR link, `file:line` evidence, concrete suggested fix. Write the report to `30 Plans/<P>/reviews/M<N>-sweep.md` (human-lane summary + machine-lane findings), then **one ticket per accepted finding** — findings that stay chat messages die in scrollback.
**Never auto-fix.** Reporting and fixing in the same pass corrupts the review; fixes are swarm-implement's job via the tickets.
their word.
re-swept before the next milestone opens; the user reads the report in the vault at their leisure. Minor findings may carry forward as open tickets.
Update flow-state either way (J1).
--- *Influences: Pocock's code-review (two-axis); Jeffallan's code-reviewer & security-reviewer & the-fool; superpowers verification-before-completion; euxx code-simplifier — see CREDITS.md.*
Your AI agents don't synchronise. SwarmVault does. One shared memory for Claude Code, Codex, and any other CLI agent. Real software engineering: requirements → design → tickets → review. 14 skills, the best of everything combined.
Systematic debugging — evidence before hypotheses, hypotheses before fixes, root cause before patches, and the diagnosis saved to the vault. Use for any real…
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System design phase — architecture, tech-stack options, module boundaries, data model, and ADRs from a validated SRS. Use after requirements are validated,…
Disconnect a project from SwarmVault and choose what happens to its knowledge — keep it, export it into the repo, or delete it. Use when the user wants to stop…
The SDLC router — figures out where a project stands and runs the right phase. Use at the START of any work in a SwarmVault project: continuing/resuming a…