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/drn/dots/plannotator-compoundnpx skills add drn/dots --skill plannotator-compoundgit clone --depth 1 https://github.com/drn/dotsWhat 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 | $0.00057 | $0.05905 |
| Opus 5 | $0.00028 | $0.02952 |
| Sonnet 5 | $0.00011 | $0.01181 |
| Haiku 4.5 | $0.00006 | $0.00590 |
Grade A, and why
plannotator-compound 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 2d 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.
This is a copy
97% identical to plannotator-compound — 13 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 575 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Compound Planning Analysis
You are conducting a comprehensive research analysis of a user's Plannotator plan archive. The goal: extract patterns from their denied plans, reduce them into actionable insights, and produce an elegant HTML dashboard report.
This is a multi-phase process. Each phase must complete fully before the next begins. Research integrity is paramount — every file must be read, no skipping.
Source Selection
Before starting the analysis, determine which data source is available.
-
Plannotator mode (first-class) — Check
~/.plannotator/plans/. If it exists and contains*-denied.mdfiles, use this mode. The entire workflow below is written for Plannotator data. -
Claude Code fallback mode — If the Plannotator archive is absent or contains no denied plans, check
~/.claude/projects/. If present, read references/claude-code-fallback.md before continuing. That reference explains how to use the bundled parser at scripts/extract_exit_plan_mode_outcomes.py to extract denial reasons from Claude Code JSONL transcripts. Every phase below has a short note explaining what changes in fallback mode — the reference file has the details. -
Neither available — Ask the user for their Plannotator plans directory or Claude Code projects directory. Do not guess.
Phase 0: Locate Plans & Check for Previous Reports
Use the mode chosen in Source Selection above.
Plannotator mode: Verify the plans directory contains *-denied.md files. If
none exist, fall back to Claude Code mode before stopping.
Claude Code fallback mode: Run the bundled parser per the fallback reference to
build the denial-reason dataset. Create /tmp/compound-planning/ if needed.
In either mode, proceed to Previous Report Detection below.
Previous Report Detection
After locating the plans directory, check for existing reports:
ls ~/.plannotator/plans/compound-planning-report*.html
What ships with it
3 files 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.
- 2d ago First seen · 575 lines · 57 tokens per session scan A 949ee3ddb68a
plannotator-compound is a skill published in the GitHub repository drn/dots (23 stars, last pushed 4d ago), licensed MIT. It adds 57 tokens to every session and 5,905 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to plannotator-compound, differing in 13 lines, and is treated as a copy.
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