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 commands/backnotprop/plannotator/plannotator-annotategit 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 | $0.00008 | $0.00311 |
| Opus 5 | $0.00004 | $0.00156 |
| Sonnet 5 | $0.00002 | $0.00062 |
| Haiku 4.5 | $0.00001 | $0.00031 |
Grade A, and why
plannotator-annotate 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.
What it actually says
Markdown Annotations
!plannotator annotate $ARGUMENTS
Your task
The output above will be one of:
- The exact text
The user approved., OR a JSON object with"decision": "approved". The user approved the markdown file. If that object also carries a"feedback"field, the user approved with notes: read them and carry them into subsequent work — they are non-blocking guidance, not a request to revise the file. Otherwise acknowledge with a single sentence ("Approved.") and stop. Either way, do not begin any work. - Empty, OR a JSON object with
"decision": "dismissed". The user closed the session without requesting changes. Acknowledge with a single sentence ("Annotation session closed.") and stop. Do not begin any work. - Plaintext annotation feedback, OR a JSON object with
"decision": "annotated"and a"feedback"field. Address the feedback. The user has reviewed the markdown file and provided specific annotations and comments. - A message that the arguments could not be resolved to a file, URL, or folder. The user described what to annotate in natural language: work out which file, URL, or folder they mean, run
plannotator annotate <path-or-url>yourself with that concrete target (keeping any flags the message echoes), then handle its output per cases 1-3.
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 · 18 lines · 8 tokens per session scan A d84563197704
plannotator-annotate is a command published in the GitHub repository backnotprop/plannotator (8,256 stars, last pushed 2d ago), licensed Apache-2.0. It adds 8 tokens to every session and 311 once invoked, about $0.0000 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 commands, from other repositories
kg-ingest
Ingest a source document into the Knowledge Graph - extract entities, concepts, create wiki pages.
kg-init
Initialize a new Knowledge Graph with raw/ and wiki/ structure.
kg-lint
Health check the Knowledge Graph - find orphans, contradictions, gaps, stale claims.
kg-project
Create a new project in the Knowledge Graph with ADR tracking.
kg-query
Query KG (supports: active, recent, search , decisions , plan ).
kg-setup
Configure Knowledge Graph path and create config file.