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.
git clone --depth 1 https://github.com/VandanaAjayDubey111/great-pmWrote 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/commands/vandanaajaydubey111/great-pm/pm-feedback)<a href="https://agentmods.dev/commands/vandanaajaydubey111/great-pm/pm-feedback"><img src="https://agentmods.dev/badge/commands/vandanaajaydubey111/great-pm/pm-feedback/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/vandanaajaydubey111/great-pm/pm-feedback"><img src="https://agentmods.dev/badge/commands/vandanaajaydubey111/great-pm/pm-feedback.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00030 | $0.00762 |
| Opus 5.5 | $0.00012 | $0.00305 |
| Sonnet 5.5 | $0.00006 | $0.00152 |
| Haiku 4.5 | $0.00003 | $0.00076 |
Grade A, and why
pm-feedback scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the great-pm /pm-feedback command. Turn raw user feedback into
structured themes.
Parse arguments
<input-source>(required) → path to feedback file (CSV, NDJSON, markdown export) OR keyword likesupport,survey,social,sales(the agent knows where these live by convention or asks).--since=<YYYY-MM-DD>(optional) → filter to feedback after this date.
Pre-flight
SRC="${1:?usage: /pm-feedback <input-source> [--since=<YYYY-MM-DD>]}"
[ -f "$SRC" ] && echo "FILE_OK" || echo "SOURCE_KEYWORD"
mkdir -p .great-pm/drafts
If SOURCE_KEYWORD, the agent will ask the user which file or stream
provides that source.
Operating procedure
-
Step 0 — refine the user's query (transparent Mode B). Invoke
query-refiner-pmwith$ARGUMENTS. The refiner returns:You typed: <original> Refined to: <refined brief> What changed: <one line> Proceeding with refined. Reply "use original" to override.Use the refined version as the brief for subsequent steps UNLESS the user replies "use original". Log the refinement to
.great-pm/refinements/$(date +%Y-%m-%d).log. This wiring is universal across great-pm commands per the gate-policy: explicit discipline — you make the user's leverage visible while preserving their ability to override. -
feedback-synthesizer
- Brief: read the feedback batch. For each item:
- Tag with JTBD (Jobs-to-be-done) it relates to.
- Severity (blocker / pain / nice-to-have).
- Sentiment (frustrated / neutral / delighted).
- Verbatim quote (preserved).
- Cluster by JTBD. For each cluster:
- Theme name.
- Frequency count.
- Severity distribution.
- Top 2 verbatim quotes.
- 1-line synthesis of what users actually want (vs. what they asked).
- Output:
.great-pm/drafts/feedback-synthesis-<YYYY-MM-DD>.md.
- Brief: read the feedback batch. For each item:
-
Surface the top 3 themes as a one-screen executive summary.
-
Suggest follow-up: if any theme is high-severity + high-frequency, recommend
/pm-discoverwith--focus=<theme>to dig deeper.
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.
- 1mo ago First seen · 82 lines · 30 tokens per session scan A 51cc608f7c4e
pm-feedback is a command published in the GitHub repository VandanaAjayDubey111/great-pm (3 stars, last pushed 1mo ago), licensed MIT. It adds 30 tokens to every session and 762 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-21.
Other commands, from other repositories
poc
Before building on an unproven idea, get a timeboxed yes/no answer — start a hypothesis-driven POC that skips 80% of the production pipeline and forces ship/pivot/kill at expiry, then promote a shipped POC through the audits it skipped.
rfc
RFC process for cross-team decisions. Create, track, and close RFCs. Accepted RFCs auto-create ADRs.
exception
Signed gate-exception registry — replace ad-hoc --admin / --no-verify bypasses with an auditable, signed, expiring record (who · why · gate · scope · expiry). Create / list / check exceptions.
new-track
Create a new development track with spec, plan, and metadata.
conductor-new-track
Create a new development track with spec, plan, and metadata.
dashboard
Starts the live web dashboard for the current fellowship — quest/scout progress, gate approvals, and event history — in the background, and prints the URL.