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 skills add byerlikaya/claude-starter-kit --skill spec-planninggit clone --depth 1 https://github.com/byerlikaya/claude-starter-kitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/byerlikaya/claude-starter-kit/spec-planning)<a href="https://agentmods.dev/skills/byerlikaya/claude-starter-kit/spec-planning"><img src="https://agentmods.dev/badge/skills/byerlikaya/claude-starter-kit/spec-planning/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/byerlikaya/claude-starter-kit/spec-planning"><img src="https://agentmods.dev/badge/skills/byerlikaya/claude-starter-kit/spec-planning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 11 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
What 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 5.1 | $0.00051 | $0.00770 |
| Opus 5 | $0.00026 | $0.00385 |
| Sonnet 5 | $0.00010 | $0.00154 |
| Haiku 4.5 | $0.00005 | $0.00077 |
Grade A, and why
spec-planning 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 11d 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spec-First Planning
Trigger phrases: "plan", "spec", "task breakdown", "acceptance criteria", "roadmap", "how do we split this"
Before writing code: what will be done, how it counts as "done", and in what order to proceed become clear.
Steps
- Purpose & scope: the problem being solved in a single sentence; also write the out-of-scope explicitly (prevent scope creep).
- Split into vertical slices: the smallest end-to-end working pieces (not horizontal layers). Each slice delivers value on its own.
- A contract for every task: input · output · measurable acceptance criterion (testable) · estimated risk.
- Dependency graph: which task waits on what; no cycles. Bring the riskiest/most-unknown to the front (fail-fast).
- Uncertainties: assumption list + open questions; do not fill ambiguous spots with a guess, ask with explicit options.
Output (docs/PLAN.md)
# <Feature> — Plan
## Acceptance criteria
- [ ] <measurable outcome>
## Tasks (order)
1. <task> — criterion: <...> — dependency: <none/#n> — risk: <low/medium/high>
## Assumptions / Open questions
- ...
Mark what you do not know — do not fill it in
Where a requirement admits more than one reading, write the marker [NEEDS CLARIFICATION: <the question>] at
that exact spot in the plan. Do not resolve it with the likeliest interpretation and move on.
This is the difference between a discipline and a hope. "Stop and ask when unsure" (§1) depends on noticing the uncertainty in the moment; a marker survives into the artifact, where the user, a reviewer and a later session can all see it. A plausible assumption silently written into a spec is indistinguishable from a decision, and that is exactly how the wrong feature gets built correctly.
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.
- 11d ago First seen · 57 lines · 51 tokens per session scan A afd60bd498f2
spec-planning is a skill published in the GitHub repository byerlikaya/claude-starter-kit (22 stars, last pushed today), licensed MIT. It adds 51 tokens to every session and 770 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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