Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/swingerman/engineer/refinenpx skills add swingerman/engineer --skill refinegit clone --depth 1 https://github.com/swingerman/engineerWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00051 | $0.01586 |
| Opus 5 | $0.00026 | $0.00793 |
| Sonnet 5 | $0.00010 | $0.00317 |
| Haiku 4.5 | $0.00005 | $0.00159 |
Grade A, and why
refine scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
refine
Charter-bound clean-up of a feature's changed code — Checkpoint 6. Modeled on Claude Code's stock /simplify (a three-subagent parallel review) with two layers the stock skill lacks: charter validation of every proposal, and graceful breaking changes.
The behavior contract (ACs + specs) is sacred — a refactor that breaks it is a category error. New shapes are introduced alongside old, never instead of.
When to use
Checkpoint 6, after atdd:atdd-team produces passing code, before crap-analyzer (Checkpoint 7).
Verification independence: if manifest.verification.apply_to_checkpoints includes 6, refine must run on a non-implementer agent. The three review subagents (Step 2) are fresh regardless, so independence is satisfied by construction.
Not for: changing behavior (feature-edit); risk analysis (crap-analyzer); code that isn't implemented/green yet.
Workflow
Step 0 — Entry gate. Before starting, verify the prior checkpoint is complete: run ${CLAUDE_PLUGIN_ROOT}/scripts/dae_handoff.py <feature-dir> --through 5. On a non-zero exit, stop and surface the gap to the human — do not proceed.
Verify branch hygiene: run ${CLAUDE_PLUGIN_ROOT}/scripts/dae_branch.py <feature-dir>.
On a non-zero exit, stop and surface the message to the human — switch
branches and re-invoke. The check honors the git.manual: true manifest
opt-out.
After the gate passes, show the pipeline breadcrumb: run
${CLAUDE_PLUGIN_ROOT}/scripts/dae_progress.py <feature-dir> and present its
output to the human — it shows where this checkpoint sits in the DAE pipeline.
The breadcrumb is advisory: a non-zero exit or a missing progress.md never
blocks the skill. Then create one TodoWrite todo per workflow step below. See
${CLAUDE_PLUGIN_ROOT}/references/progress-indicator.md.
- Resolve + scope — resolve the methodology root + manifest via
${CLAUDE_PLUGIN_ROOT}/scripts/dae_resolve.py(seereferences/resolving.md); locate the feature. Scope = the feature branch's changed code (git diffagainst the branch point). Loadfeature.md,acs.md,spec.md,CHARTER.md. - Dispatch three parallel review subagents (
superpowers:dispatching-parallel-agents), each over the same changed code. Before dispatching, run${CLAUDE_PLUGIN_ROOT}/scripts/dae_dup.py <methodology-root>to get deterministic project-wide duplicate findings; pass the JSON result into the Reuse subagent's context as a tool input (the subagent treats it as one signal alongside its own LLM judgment, and produces a unified set of findings — not a separate list). Ifdae_dup.pyreturns anything other thanstatus: ok—status: unavailable(the backend tool isn't installed),status: skipped(manifestduplication.skip: true),status: unsupported(the configured backend isn't implemented in this version), orstatus: error(scan failed) — surface that status in the Reuse subagent's prompt and proceed with its existing LLM-only judgment.- Reuse — duplication (LLM +
dae_dup.pyfindings), reinvented wheels, dead code, missed existing utilities. LSP-first lookup — at dispatch time, check whether an LSP MCP capability is available; pass that detection result and the LSP-first preference into the Reuse subagent's prompt so it uses find-references / workspace-symbols when available, with graceful fallback to grep + Read. See${CLAUDE_PLUGIN_ROOT}/references/code-lookup.md. - Quality — clarity, structure, naming, incidental complexity, maintainability
- Efficiency — redundant computation, repeated lookups, visible performance smells
- Reuse — duplication (LLM +
- Consolidate — merge findings; dedup overlaps (note multi-lens hits as strong signals); keep genuine conflicts as alternatives for the human.
- Charter filter — check every proposal against
CHARTER.md(architecture, conventions, methodology, the ACs+specs contract). Charter-violating proposals are rejected internally — never shown. This filter is the DAE-specific layer the stock skill lacks. - Classify breaking changes — consumer-facing (something outside the blast radius depends on the old shape) → graceful path: deprecation-marked forwarding shim + migration note, new shape alongside old. Internal-only → hard change is fine.
- Present; human picks — show charter-compliant proposals (change, why, blast radius, churn). The human selects which are worth the churn.
- Apply — apply selected; install graceful paths where needed; re-run both test streams. Before running the test streams, ensure required infra is up: read
manifest.yml'sinfra:section, then call${CLAUDE_PLUGIN_ROOT}/scripts/dae_infra.py ensure <names>for each declared dependency the tests need. On astart-failedstructured failure → stop and surface the diagnosis. On a missing manifest declaration for required infra → stop with the "declare in manifest" message. Any failure → revert that proposal and report. - Handoff — emit a summary.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 64 lines · 51 tokens per session scan A 790d3e98f1a7
refine is a skill published in the GitHub repository swingerman/engineer (144 stars, last pushed 6d ago), licensed MIT. It adds 51 tokens to every session and 1,586 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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