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 dcosson/h2 --skill plan-incorporategit clone --depth 1 https://github.com/dcosson/h2Wrote 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/dcosson/h2/plan-incorporate)<a href="https://agentmods.dev/skills/dcosson/h2/plan-incorporate"><img src="https://agentmods.dev/badge/skills/dcosson/h2/plan-incorporate.svg" alt="Measured on agentmods" 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 Tool Misuse · line 151 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
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 | $0.00052 | $0.01736 |
| Opus 5 | $0.00026 | $0.00868 |
| Sonnet 5 | $0.00010 | $0.00347 |
| Haiku 4.5 | $0.00005 | $0.00174 |
Grade A, and why
plan-incorporate 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 8d 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 — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Incorporate
Incorporate review feedback into a plan doc and its test harness. Add a disposition table for the current round, clean up review files.
Inputs
$0: Doc identifier (e.g.,04d-oltp-sql-engine)$1,$2, ...: Review file paths to incorporate (or omit to auto-discoverdocs/plans/$0-review-*.mdanddocs/plans/$0-test-harness-review-*.md)- Plans directory:
docs/plans/(or the project's established plans directory)
Phase 1: Discover & Read
- Read the source plan doc
docs/plans/$0.mdand test harnessdocs/plans/$0-test-harness.md(if exists) - Detect existing disposition tables — scan for
## Review Dispositionor## Round N Review Dispositionheaders. Count how many rounds already exist (0, 1, 2, ...). The current incorporation is Round N+1. - Find all review files for the current round:
docs/plans/$0*review*.md(design reviews + TH reviews). These are the files that haven't been incorporated yet. - Read ALL current-round review files
- Read existing disposition tables to understand what has already been decided in prior rounds
Phase 2: Evaluate Each Finding
Key principle: respect prior decisions. Do not re-litigate findings from earlier rounds. The disposition tables from prior rounds represent settled decisions.
For every finding in the current round's review files:
- Check if it duplicates a prior-round finding — if the same issue was already dispositioned in an earlier round, skip it (do NOT add to the new disposition table)
- Check if already addressed in the current doc text
- If valid and not yet addressed — plan to incorporate the change into the source doc
- If the finding disagrees with a prior-round disposition — only re-open if the reviewer makes a compelling case that the prior decision was genuinely wrong at P1+ severity. Do not bikeshed on settled decisions. If re-opening, note which prior finding it overrides.
- If intentionally not incorporating — prepare the rationale
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 155 lines · 52 tokens per session scan A b23a89b4fde3
plan-incorporate is a skill published in the GitHub repository dcosson/h2 (159 stars, last pushed 12d ago), licensed MIT. It adds 52 tokens to every session and 1,736 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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