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/nmrtn/nanopm/pm-add-feedbacknpx skills add nmrtn/nanopm --skill pm-add-feedbackgit clone --depth 1 https://github.com/nmrtn/nanopmWrote 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/nmrtn/nanopm/pm-add-feedback)<a href="https://agentmods.dev/skills/nmrtn/nanopm/pm-add-feedback"><img src="https://agentmods.dev/badge/skills/nmrtn/nanopm/pm-add-feedback.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 | $0.00162 | $0.07386 |
| Opus 5 | $0.00081 | $0.03693 |
| Sonnet 5 | $0.00032 | $0.01477 |
| Haiku 4.5 | $0.00016 | $0.00739 |
Grade C, and why
pm-add-feedback scanned grade C with 2 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.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
{ echo "ERROR: nanopm not installed. Run: curl -fsSL https://raw.githubusercontent.com/nmrtn/nanopm/main/setup | bash"; exit 1; } Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
{ echo "ERROR: nanopm not installed. Run: curl -fsSL https://raw.githubusercontent.com/nmrtn/nanopm/main/setup | bash"; exit 1; } How it starts
The opening of the file, as written. The whole thing — 473 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Multi-host portability rules. When invoking
AskUserQuestion:
- The
headerfield MUST be a short noun phrase (≤ 12 characters). Mistral Vibe rejects longer headers withstring_too_long. Pick from:Start,Target,Scope,Audience,Methodology,Feature,Question,Confirm,Intake.- The
optionslist MUST have at least 2 items. Vibe rejects empty/single-option calls. For free-text input, always provide ≥ 2 framing options (e.g.Yes, here's the input/Skip) — never callask_user_questionwithoptions: [].
Preamble (run first)
source ~/.nanopm/lib/nanopm.sh 2>/dev/null || \
source .nanopm/lib/nanopm.sh 2>/dev/null || \
{ echo "ERROR: nanopm not installed. Run: curl -fsSL https://raw.githubusercontent.com/nmrtn/nanopm/main/setup | bash"; exit 1; }
nanopm_preamble
_OPP_DIR=".nanopm/wiki/entities/opportunities"
_BIN="$HOME/.nanopm/bin"
What this skill does
/pm-add-feedback is the single ingestion door for raw user signal. Whatever the form — an
interview transcript, a pasted Slack DM, a support ticket, a Gong export, a feedback email — it comes
in here, and every run ends the same way: the source is archived verbatim and the opportunity DB
is grounded in fresh, verifiable verbatims, with the source cross-linked to every opportunity it
touched. This is the learning loop the PRD
(.nanopm/wiki/docs/prds/feedback-ingestion-and-learning-loop.md) calls non-negotiable.
The loop, every time:
- INTAKE — resolve a file path,
--pastetext, or a connector source to raw content. - ARCHIVE (Wave-0 API) —
nanopm_archive_raw <type> <source>drops the bytes underraw/<type>/<id>.<ext>keyed by a content hash (idempotent), before any extraction. Everything below cites back to that file. - EXTRACT (Mom-Test discovery filter) — pull problems / past behaviors with their verbatim
quotes; demote feature-requests and speculation. Each kept claim carries a citation of the exact
form
"<verbatim>" — <source>, <date>that resolves to the archived raw file. - PASS 1 — ground existing opportunities (default, highest-value path) — for each problem, judge it
against the existing DB; a confident match is a candidate to ground (append verbatim, propose a
provenance upgrade
nano-hypothesis → evidence-backed). This is a judgement — the write itself is delegated (see DELEGATE). - PASS 2 — surface new opportunities (strategy-aware) — for unmatched signal, judge whether it deserves a NEW opportunity grounded in vision / strategy / objectives — only when the signal is both unmatched AND strategy-coherent. Again a judgement; the write is delegated.
- CONFIRM — ONE batched confirmation (accept all / edit / reject) before any write; uncertain
matches carry
⚠ low-confidence. Headless (no TTY / viewer) runs fall back to write-then-review (delegate with⚠ low-confidence, no blocking prompt). - DELEGATE —
/pm-add-feedbackdoes NOT write opportunity files itself. For each confirmed candidate it hands the problem + verbatim/citation + raw-source ref + suggested provenance to/pm-opportunities --ingest-candidate(Change 1's "ingest confirmed candidate" entry), which is the single owner of the opportunity DB. That entry runs the full canonical process — dedup-with- confidence, match-or-create,related_to, SCHEMA conformance, reindex, the entity LOG line, AND the bidirectionalnanopm_raw_manifestsource→opportunity link — and returns a per-candidate result. - SUMMARY — emit a machine-readable run-summary (archived raw path, opportunities created/updated,
provenance transitions, themes) — assembled from the per-candidate results
/pm-opportunitiesreturned — AND persist it viananopm_context_append— the linchpin the viewer digest parses.
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 · 473 lines · 162 tokens per session scan C a6502e8b7a2e
pm-add-feedback is a skill published in the GitHub repository nmrtn/nanopm (48 stars, last pushed 1mo ago), licensed MIT. It adds 162 tokens to every session and 7,386 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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