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/backnotprop/plannotator/plannotator-compoundnpx skills add backnotprop/plannotator --skill plannotator-compoundgit clone --depth 1 https://github.com/backnotprop/plannotatorWhat 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 | $0.05946 |
| Opus 5 | $0.00028 | $0.02973 |
| Sonnet 5 | $0.00011 | $0.01189 |
| Haiku 4.5 | $0.00006 | $0.00595 |
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- plannotator-compound — 97% identical, 13 lines differ
How it starts
The opening of the file, as written. The whole thing — 576 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) — Determine the Plannotator data directory: use
$PLANNOTATOR_DATA_DIRif set, otherwise~/.plannotator. Check theplans/subdirectory there. 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.
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 · 576 lines · 57 tokens per session scan A 230a73ccb90e
plannotator-compound is a skill published in the GitHub repository backnotprop/plannotator (8,341 stars, last pushed today), licensed Apache-2.0. It adds 57 tokens to every session and 5,946 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.
Other skills, from other repositories
cache-notes
Fetch & embed AI transcripts as Obsidian callouts. Args: , all, refresh . Prompts for URLs if empty.
followup-todos
Extract action items as plain markdown bullets (with confirmation). Args: . No args = run /note-status pending --step=todos.
meeting
Create or wrap meeting notes. Args: {title} [folder=X], wrap , wrap pending [today|this week|dates]. No args = pick from Google Calendar.
organize-meetings
Triage Meetings/inbox/ — move each file to the correct subfolder by finding adjacent/similar notes via qmd, applying learned routing conventions from memory, and confirming with the user.
recap
Produce a weekly/date-range recap from emails, Slack, Jira/Confluence, and vault notes. Args: [dates]. Default = this week.
sprint-retro
Draft a Sprint Retro by synthesizing scrum dailies, recaps, the sprint planning note, and the prior retro. Args: [sprint number | dates]. No args = infer the current sprint.