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 skills add drivestream-lab/prayog-skills --skill post-product-questionsgit clone --depth 1 https://github.com/drivestream-lab/prayog-skillsWrote 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/drivestream-lab/prayog-skills/post-product-questions)<a href="https://agentmods.dev/skills/drivestream-lab/prayog-skills/post-product-questions"><img src="https://agentmods.dev/badge/skills/drivestream-lab/prayog-skills/post-product-questions/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/skills/drivestream-lab/prayog-skills/post-product-questions"><img src="https://agentmods.dev/badge/skills/drivestream-lab/prayog-skills/post-product-questions.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 | $0.00109 | $0.01154 |
| Opus 5.5 | $0.00044 | $0.00462 |
| Sonnet 5.5 | $0.00022 | $0.00231 |
| Haiku 4.5 | $0.00011 | $0.00115 |
Grade A, and why
post-product-questions 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 2mo 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Post product questions (PE → Meta PR)
PE closes the engg-reviews loop by publishing codebase-grounded product questions on the Meta PRD PR and asking PM for feedback.
This is not a PM decision skill. Do not walk AskQuestion accept/reject
loops. Do not edit prd/INIT-*.md or outlines. Do not run
/validate-requirements, /review-findings, or /update-documents.
Question shape: ../references/product-question-template.md.
Handoff: ../references/handoff-adjunct.md.
Lane split
| Role | Action |
|---|---|
| PE | Map → optional /review-product-questions → this skill posts on Meta PR |
| PM (later, meta) | Read PR comments → update PRD + outline → requirements skills |
| Gate 1 | Unchanged — still impact-map-lgtm + Approve; this post does not unlock it |
NON-NEGOTIABLE
- Input is one
/prd-codebase-mapartifact — do not re-run graphs. - Include for each Q: scenario, example, recommendation, why, alternatives, evidence (so PM can decide without reading code).
- No product decisions in this skill — recommendations are PE proposals only.
- No PRD / outline edits.
- GitHub comment (or draft body file) only after explicit PE authorization.
- Never set/clear
impact-map-*orspec-*labels. gate_coupled: falsealways.- Dual output: local body file under pe-workspace
out/reports/+ Meta PR comment when authorized.
Inputs
- Map path — (REQUIRED)
PRD-Codebase-Map-{INIT}.md - PE stance — (OPTIONAL)
PE-Product-Stance-{INIT}.mdfrom/review-product-questions. When present, prefer refined recommendations and omit dropped questions. - Meta PR — (REQUIRED) number/URL + repo (e.g.
autrio10x/drivestream-meta#104) - Mode — all questions / conflicts-only / PE-selected IDs
Process
T0 — Gather
- Parse § Product questions from the map.
- If stance file exists, overlay pe_action / refined recommendations; skip
drop-questionrows. - Resolve Meta PR via
gh pr viewwhen available. - Cap: post the same capped set as the map (default ≤10).
What ships with it
1 file 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.
- 2mo ago First seen · 115 lines · 109 tokens per session scan A 1792c9017a49
post-product-questions is a skill published in the GitHub repository drivestream-lab/prayog-skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 109 tokens to every session and 1,154 once invoked, about $0.0004 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 2026-08-31.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…