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/darkroomengineering/cc-settings/plan-featurenpx skills add darkroomengineering/cc-settings --skill plan-featuregit clone --depth 1 https://github.com/darkroomengineering/cc-settingsWhat 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 | $0.00067 | $0.02516 |
| Opus 5 | $0.00034 | $0.01258 |
| Sonnet 5 | $0.00013 | $0.00503 |
| Haiku 4.5 | $0.00007 | $0.00252 |
Grade A, and why
plan-feature 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 — 325 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Feature
Two-phase pre-implementation planning: clarify requirements via interview, then compile a complete PRD.
Phase 1: Discovery
Help clarify requirements and scope through structured questioning.
Interview Framework
The interview is a fog-of-war walk across four quadrants of the unknown. Open by listing the known knowns (what the user has already decided), then work the questions below to surface known unknowns (open questions they're aware of), unknown knowns (constraints they hold but haven't said — the questions in 2–4 exist to shake these loose), and close by hunting unknown unknowns ("what would surprise us mid-build? what reference implementation should we read first?"). A discovery that ends with all four quadrants visited produces a PRD that doesn't get re-planned in week two.
Goal Quality Bar (gate before interviewing)
Before opening the interview questions below, try to state the goal in one line that answers five things:
- What's true when this is done?
- What evidence shows it — a command, a test, a metric, a reviewed artifact?
- What threshold counts as success — pass/fail, or a number?
- What's explicitly out of scope, where that would matter?
- What's the stop condition — the point where you ask the user instead of guessing?
If a clean one-liner falls out, skip straight to Phase 2's clarifying questions — the interview below exists for when it doesn't.
Reject pure activity goals — "make progress," "keep investigating," "improve things" — until sharpened into a verifiable outcome:
- Weak: "Make checkout faster." Sharpened: "Reduce checkout API p95 latency below 250ms for the documented slow path, verified with
npm run test:checkoutand 3 consecutive benchmark runs under 250ms." - Weak: "Clean up the auth code." Sharpened: "Resolve the open change-request threads on PR 123, touching only the affected auth files and tests, verified with the targeted auth test command plus
gh pr view 123showing no unresolved threads."
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 · 325 lines · 67 tokens per session scan A 9b09f643b57e
plan-feature is a skill published in the GitHub repository darkroomengineering/cc-settings (42 stars, last pushed 4d ago), licensed MIT. It adds 67 tokens to every session and 2,516 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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