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 smartwhale8/claude-playbook --skill plan-featuregit clone --depth 1 https://github.com/smartwhale8/claude-playbookWrote 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/smartwhale8/claude-playbook/plan-feature)<a href="https://agentmods.dev/skills/smartwhale8/claude-playbook/plan-feature"><img src="https://agentmods.dev/badge/skills/smartwhale8/claude-playbook/plan-feature/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/smartwhale8/claude-playbook/plan-feature"><img src="https://agentmods.dev/badge/skills/smartwhale8/claude-playbook/plan-feature.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00036 | $0.00509 |
| Opus 5.5 | $0.00014 | $0.00204 |
| Sonnet 5.5 | $0.00007 | $0.00102 |
| Haiku 4.5 | $0.00004 | $0.00051 |
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 1mo 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.
What it actually says
Plan a feature
The idea: $ARGUMENTS
Claude solving the wrong problem well is the most expensive failure in an agentic session. This skill spends a few minutes preventing it.
1. Read before asking
Find how the codebase already does the nearest equivalent thing. Identify the files a change like this would touch and the patterns it should follow. Bring that to the interview, so the questions are about the decisions rather than the facts.
2. Interview
Use AskUserQuestion to work through what is genuinely undecided. Skip anything you can answer by reading the code.
Cover:
- Behaviour. What happens in the normal case, and at each edge the user cares about.
- Scope. What is explicitly not part of this.
- Data. What is stored, what is derived, what migrates.
- Interface. The endpoints, the screens, or the commands involved.
- Failure. What happens when the dependency is down, the input is bad, or the operation is repeated.
- Verification. What has to be true for this to be finished.
Keep going until the hard parts are decided. Stop asking about things that have one obvious answer.
3. Write the specification
Write SPEC.md in the repository root:
# <Feature>
## Goal
One paragraph. What this enables and for whom.
## Out of scope
The explicit list.
## Files and interfaces
Each file to add or change, and what changes in it.
## Behaviour
Numbered cases, each with its expected result.
## Data
Schema changes, migrations, derived values.
## Failure modes
Each one and the intended handling.
## Acceptance criteria
A numbered list, each item verifiable by a command or an observation.
## Verification
The end-to-end check that proves the feature works.
4. Hand over
Tell the user to start a fresh session to implement it, pointing that session at SPEC.md. A clean context that reads a good specification outperforms a long context that wrote one.
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.
- 1mo ago First seen · 69 lines · 36 tokens per session scan A f4b6dda3be34
plan-feature is a skill published in the GitHub repository smartwhale8/claude-playbook (43 stars, last pushed 1mo ago), licensed MIT. It adds 36 tokens to every session and 509 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-21.
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