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/kv0906/pm-kit/explainnpx skills add kv0906/pm-kit --skill explaingit clone --depth 1 https://github.com/kv0906/pm-kitWhat 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 | $0.00055 | $0.00838 |
| Opus 5 | $0.00028 | $0.00419 |
| Sonnet 5 | $0.00011 | $0.00168 |
| Haiku 4.5 | $0.00006 | $0.00084 |
Grade A, and why
explain 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.
How it starts
The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Explain — First Principles Concept Breaker
Reverse-engineer complex concepts into natural language. No jargon. Start from the end result and work backwards to raw inputs.
Input format: /explain [concept, formula, model, or paste]
What You Do
Take any complex input — math formula, scoring model, system design, methodology, technical concept — and explain it so a beginner can explain it back.
Input
User provides:
- A math problem, equation, methodology, scoring system, model, or abstract concept
- Optional: context of what it's used for (finance, physics, prediction markets, etc.)
Reasoning Process (follow in order)
Work through these steps internally before writing the explanation:
A. Find the End Goal — What is the final output? Translate it to a real-world result (money, score, probability, decision, ranking).
B. Find the Inputs — What raw information goes in? Translate each to real-world meaning.
C. Find How Value Is Earned — What actions/factors increase the result? What decreases it?
D. Find Comparisons — Does the model compare things? (person vs person, side vs side, time vs time). Explain as "share of total" or "relative contribution".
E. Find Rules and Boundaries — Minimums, maximums, penalties, special cases. Explain why each exists.
F. Find Time/Repetition — If the model samples repeatedly, explain as "measured many times and added up over time."
G. Find What Breaks Without Each Piece — For each major component, ask: what goes wrong if we remove this? This reveals WHY it exists.
Output Structure
Write these sections in order:
1. What This Produces
One sentence: what the final output represents in real life.
2. What Controls It
List the real-world factors that push the result up or down. No symbols.
3. Reverse Walkthrough (End → Beginning)
Start from the final result. Walk backwards through each layer until reaching raw inputs. Each step should answer: "where does THIS come from?"
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 · 98 lines · 55 tokens per session scan A 8c8dfdd7fed0
explain is a skill published in the GitHub repository kv0906/pm-kit (133 stars, last pushed 2mo ago), licensed MIT. It adds 55 tokens to every session and 838 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
critique-agent
Pressure-test an existing product brief or PRD pack — find gaps, hidden assumptions, inconsistencies, and failure modes before stakeholder review. Use when: critique brief, critique PRD, devils advocate, red team, pressure test, find holes, what could go wrong, stress test the doc, pre-mortem.
interview-frameworks
Frameworks for user interviews, question design, and qualitative research. Use when conducting user interviews, designing interview guides, researching user needs, or gathering qualitative insights. Trigger on: 'create an interview guide', 'how do I interview users', 'customer discovery questions', 'user research…
query-datasets
Answer grounded yes/no questions about what exists in the 03-datasets/ example corpora (supporttickets, calltranscripts) using the local SQLite + FTS5 + vector hybrid index. Use when the user asks 'do/does [corpus] contain/mention/include/have requests for X?', 'any [corpus] about Y?', or similar factual queries over…
critique-prd
Rubric-score a PRD pack (02 + 03) against the 7-dimension PM Brain rubric and run a 4-persona panel review. Returns scores, panel critiques, the single weakest section, a concrete rewrite, and P0/P1 fix lists. Use when: PRD review, score my PRD, rubric review, panel review, rewrite weakest section, critique-prd.
create-prd
Write the PRD pack (02-product-requirements.md + 03-success-metrics.md) on top of an approved product brief. Use when: PRD, product requirements, requirements doc, success metrics, spec writeup, shape the PRD.
create-internal-feature-announcement
Drafts an internal feature announcement (IFA) from the PRD pack and user sources using the repo template, then writes 04-internal-feature-announcement.md. Use when: IFA, internal feature announcement, internal FAQ, Slack IFA prep, launch comms pack, or internal product documentation from the template.