| name | swarm-implement |
| description | Execute complex implementation work with a swarm-like Claude Code workflow: parallel exploration, scoped planning, selective deep validation, and independent reviewer/critic checks where risk justifies them. Use for feature work, bug fixes, refactors, and multi-file changes. |
/swarm-implement
Use this skill for implementation work when you want Claude Code to behave like a fast, high-quality swarm rather than a single-threaded assistant.
Purpose
Complete real coding tasks across many projects while preserving Claude Code speed and adding swarm-style quality discipline.
Core operating model
Use this execution ladder:
- Explore in parallel.
- Build a scoped plan.
- Implement in small, coherent units.
- Run objective validation.
- Use independent reviewer validation where the risk justifies it.
- Use critic challenge only for high-impact or still-ambiguous results.
- Synthesize and report what changed, what was verified, and what remains risky.
This is not a slow full-swarm recreation.
This is a speed-preserving, quality-maximizing workflow.
Quality and speed policy
- Quality and pre-ship defect detection are paramount.
- Speed still matters.
- Parallelism is the default speed lever.
- Deep validation is concentrated where bugs are expensive.
- Low-risk work should stay lightweight when extra depth would not materially improve quality.
- High-risk work must always get the deeper validation path.
High-risk work
Always use the deeper validation path for:
- auth, authz, identity, sessions, permissions
- payments, billing, money movement, destructive actions
- dependency changes, install scripts, lockfile changes
- public API changes, schema changes, migrations
- concurrency, queues, retries, state machines, caching
- file access, subprocesses, parsing, secrets, security-sensitive logic
- large cross-file refactors with correctness risk
Recommended workflow
Phase 0 — Establish scope
Determine the exact task scope first:
- what changed or needs to change
- what files are likely involved
- what success looks like
- what must not be broken
- what verification is required
If the task is unclear, ask a small number of targeted questions or create a short written plan before coding.
Phase 1 — Parallel exploration
Launch parallel subagents for disjoint investigation tasks such as:
- repository mapping for relevant subsystems
- locating existing patterns to follow
- finding tests, schemas, contracts, and integration points
- identifying likely side effects and touched modules
- checking dependency or migration implications
Do not use the main thread for broad repo reading if subagents can do it.
Keep the main context focused.
Merge-base-aware scope: When analyzing a PR branch, scope the diff to the
correct commit range — use git merge-base origin/master HEAD to find the
divergence point, then use the three-dot diff origin/master...HEAD to exclude
upstream changes. Never use the full branch accumulation (master..HEAD) which
includes merge artifacts from prior PRs and causes wasted exploration. Record
the base ref, head ref, and commit range explicitly for downstream explorers.
Phase 2 — Plan
Create a concrete implementation plan before editing for any non-trivial task.
The plan should include:
- files to change
- intended behavior
- risks and likely regressions
- validation commands
- whether reviewer and critic passes will be required
Phase 3 — Implement in scoped units
Implement in coherent, reviewable chunks.
Avoid giant speculative rewrites.
Follow existing repository patterns unless there is a strong reason not to.
Phase 4 — Objective validation
Always run the strongest objective checks available for the task:
- tests
- lint
- typecheck
- build
- targeted repro scripts
- local runtime verification where relevant
If you cannot verify it, do not claim it is done.
Phase 5 — Independent reviewer validation
Use an independent reviewer subagent when the task is:
- high-risk
- cross-file
- behavior-sensitive
- likely to hide edge-case bugs
- security-sensitive
- likely to produce false confidence from the implementation context
Reviewer responsibilities:
- inspect the implementation with fresh context
- look for correctness bugs, edge cases, regressions, claim-vs-actual mismatches, and test blind spots
- be hyper-critical and suspicious
- default to disbelief until evidence supports the change
- identify whether issues are CONFIRMED, DISPROVED, UNVERIFIED, or PRE_EXISTING when useful
Phase 6 — Critic challenge
Use a critic subagent only when needed:
- reviewer found high-impact issues
- confidence is still borderline
- the change touches high-risk systems
- the implementation appears polished but may hide requirement drift or false confidence
Critic responsibilities:
- challenge reviewer-confirmed findings
- look for severity inflation, weak evidence, missing sibling-file checks, and poor actionability
- prefer removing weak claims over adding noise
Phase 7 — Final synthesis
In the main thread, summarize:
- what changed
- what was verified
- what reviewers found
- what critic challenged
- final remaining risks
- whether the task is actually complete
Hard rules
- Do not let implementation context self-approve high-risk work.
- Do not skip reviewer validation for high-risk work.
- Do not skip objective verification because the code looks right.
- Do not let perceived repo size or task size compress the workflow.
- If quality and speed conflict, quality wins.
- If extra validation does not materially improve quality, keep the path lightweight.
Suggested subagent prompts
Explorer-style
Use for broad discovery:
- map the assigned subsystem quickly
- identify likely files, patterns, contracts, tests, and risks
- return a concise actionable summary
- do not edit code
Reviewer-style
Use for implementation validation:
- review the implementation with fresh context
- be hyper-critical and suspicious
- look for edge cases, regressions, hidden coupling, and claimed-vs-actual mismatches
- verify whether the tests actually prove behavior
- return only high-signal findings
Critic-style
Use for final challenge:
- challenge high-impact conclusions
- check whether findings are overclaimed or weakly evidenced
- challenge severity and actionability
- look for what the previous layer may have missed
Use across many repos
This skill is intentionally project-agnostic.
It should adapt to each repository by exploring first, following local patterns, and scaling validation depth to actual risk.