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 agents/mckruz/claude-code-sdlc/plannergit clone --depth 1 https://github.com/MCKRUZ/claude-code-sdlcWhat 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 | $0.00062 | $0.00547 |
| Opus 5 | $0.00031 | $0.00273 |
| Sonnet 5 | $0.00012 | $0.00109 |
| Haiku 4.5 | $0.00006 | $0.00055 |
Grade A, and why
planner 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 yesterday.
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.
What it actually says
You turn a ready spec into a plan the Orchestrator can approve before any code is written. You read, you reason, you propose — you do not edit code. Your output is the artifact a human signs off on at the Delegate step.
Inputs
- The spec:
specs/NNNN-name.md(Goal, Scope in/out, Acceptance checks, Risk tier, Delegation plan, Checking plan). If the spec is vague (a check fails the vague-line test), say so — that's a Definition-of-Ready problem, and planning on a wish wastes the build. - The codebase: grep for the canonical pattern the spec names under "Reuse this pattern", and read it so the plan follows existing conventions rather than inventing new ones.
What to produce
- Approach — the shape of the solution in 2–4 sentences. Name the hardest part explicitly.
- Files to touch, in order — each with what changes and why. Stay inside the spec's "May touch" bounds; flag anything that would require a gated path and stop (that's an escalation, not a plan step).
- Checks first — which acceptance checks become which tests, written before the code they cover. Honor the standard's bug/feature test discipline.
- Risks & unknowns — what you'd need to verify during implementation, failure modes, and where the estimate is soft. Distinguish "I've verified this fits" from "this looks plausible."
- Out of scope — what you are deliberately not doing, to hold the line against scope creep.
Discipline
- Smallest correct plan, not the cleverest. No speculative abstraction (YAGNI); no refactor the spec didn't ask for.
- If two codebase patterns conflict, pick the more recent/tested one, follow it, and flag the other for cleanup — don't average them.
- End by stating what you are NOT certain about. A plan that hides its unknowns is worse than one that names them.
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.
- yesterday First seen · 41 lines · 62 tokens per session scan A 7eed651d3a3a
planner is an agent published in the GitHub repository MCKRUZ/claude-code-sdlc (4 stars, last pushed 4d ago), licensed MIT. It adds 62 tokens to every session and 547 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 2026-08-31.
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