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/dcosson/h2/plan-tightennpx skills add dcosson/h2 --skill plan-tightengit 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-tighten)<a href="https://agentmods.dev/skills/dcosson/h2/plan-tighten"><img src="https://agentmods.dev/badge/skills/dcosson/h2/plan-tighten.svg" alt="Measured on agentmods" 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 | $0.00095 | $0.01775 |
| Opus 5 | $0.00048 | $0.00888 |
| Sonnet 5 | $0.00019 | $0.00355 |
| Haiku 4.5 | $0.00010 | $0.00178 |
Grade A, and why
plan-tighten 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 4d 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Tighten
Surgically trim a plan doc. The git commit is the audit trail — author reverts specific chunks they disagree with. Different mental mode from plan-review (correctness) and plan-incorporate (applying review feedback): this is a focused pass on writing tightness only. Do not change technical decisions, do not re-litigate scope, do not rewrite voice — only cut.
Inputs
$0: Doc identifier (e.g.,04d-oltp-sql-engine) or path to a single plan doc- Plans directory:
docs/plans/(or the project's established plans directory)
Phase 0: Preconditions
- Refuse if uncommitted review files exist for this doc:
docs/plans/$0*review*.md. Reviews must be incorporated first — they may inform what's canonical or load-bearing. Tell the user "run /plan-incorporate first" and exit. - Refuse if the working tree is dirty for this doc.
git diff --quiet -- docs/plans/$0*.mdmust succeed. Each tighten pass should be a clean, reviewable commit so the author can revert specific chunks.
Phase 1: Read Context
- Read the target doc
docs/plans/$0.mdand its companion test harnessdocs/plans/$0-test-harness.md(if it exists) - Read the parent architecture doc and plan index — so you know what's canonical there vs. duplicated here
- Read sibling plan docs only as needed to verify candidates are duplicates (do not read everything proactively — that's a waste of context)
- Record
wc -lbaseline for the diff stats at the end
Phase 2: Identify Cut Candidates
Pass through the doc and tag candidates by pattern. Do NOT edit yet — build the full list first so Phase 3 can decide whether the total reduction is worth it.
Patterns to cut
- Review residue: "Previously open: …", "addressed in R2", parenthetical references to prior-round feedback. Once incorporated, these are noise — the disposition table is the audit history.
- Restated rationale: the same "why" appears in 3 places (motivation, summary, decision log) without each adding distinct content. Keep the canonical occurrence; cut the others or replace with a one-line cross-reference.
- Defensive justification: "Why X over Y" sections that are 10× longer than the decision warrants. Two sentences usually suffice unless Y is a non-obvious alternative a reader will independently propose.
- Pre-explained tables / table-explained prose: prose paragraph immediately followed by a table that says the same thing. Keep one (usually the table).
- Illustrative code with no non-obvious logic: a 30-line code block where the function signature + a sentence of prose conveys the same information. Cut the body, keep signature + prose. But keep code that shows non-obvious logic, ordering invariants, edge-case handling, or wire-format details.
- Duplicate code blocks: same function shown twice with small diffs across sections. Show once, note the variant in prose.
- Test enumeration verbosity: 12 bullet-points each starting "test_a_does_…" where the difference is one phrase per bullet. Group by what's covered (e.g., "test_a covers id-based dedup across 4 cases: empty seen-set, single-id seen, multi-id seen, post-compaction id …"). Keep the test count and coverage commitment; cut the per-bullet ceremony.
- Adjacent overlapping sections: "What this supersedes" + "What gets removed" + "Migration" often re-cover the same deletions. Consolidate into one section per concern.
- Stale "Open questions" entries: questions that have been answered elsewhere in the body. Move the answer to its proper section if needed, delete the open-questions entry.
- Defensive doc sections: paragraphs anticipating reviewer questions where the answer is already implicit in the design.
- Connecting phrases that don't connect: "Note that…", "It's worth mentioning…", "As discussed above…" leading into a sentence that stands on its own. Cut the lead-in.
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.
- 4d ago First seen · 102 lines · 95 tokens per session scan A a0c43a240f76
plan-tighten is a skill published in the GitHub repository dcosson/h2 (159 stars, last pushed 8d ago), licensed MIT. It adds 95 tokens to every session and 1,775 once invoked, about $0.0005 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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