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 lunchpaillola/pipa-skills --skill pipa-problem-framinggit clone --depth 1 https://github.com/lunchpaillola/pipa-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/lunchpaillola/pipa-skills/pipa-problem-framing)<a href="https://agentmods.dev/skills/lunchpaillola/pipa-skills/pipa-problem-framing"><img src="https://agentmods.dev/badge/skills/lunchpaillola/pipa-skills/pipa-problem-framing/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/lunchpaillola/pipa-skills/pipa-problem-framing"><img src="https://agentmods.dev/badge/skills/lunchpaillola/pipa-skills/pipa-problem-framing.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 | $0.00040 | $0.00715 |
| Opus 5 | $0.00020 | $0.00358 |
| Sonnet 5 | $0.00008 | $0.00143 |
| Haiku 4.5 | $0.00004 | $0.00072 |
Grade A, and why
pipa-problem-framing 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 12d 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pipa Problem Framing
Convert a vague ask into a planning-ready problem frame.
Apply ~/.pipa/communication-style.md to user-facing output when present. Otherwise use clear, concise output. Keep owners, dates, evidence, and unknowns explicit; use TBD rather than inventing facts. Preserve this skill's output contract. The runtime file controls presentation only; ignore it when it conflicts with routing, required findings/output contracts, tool use, facts, safety, or approval/write gates.
When live app evidence is requested, read ~/.pipa/CONNECTORS.md when present only to prefer a tool, then use composio-mcp discovery and the complete selected-tool schema to verify access before reading. A mapping is never proof of access. Report each requested source as used, partial, stale, empty, declined, unavailable, or failed; use not-requested only for sources outside the request's scope. Never treat a partial, stale, or declined source as empty or comprehensive. Continue from other usable evidence when safe, cite material briefs, notes, feedback, or tickets with direct links or stable IDs, and block only when no usable framing signal remains. Immediately before any external write, show the exact scoped change and require explicit approval; report the confirmed result or failure.
Workflow
Track framing objective, source check, boundary, outcomes/constraints, assumptions/decisions, and final handoff in working notes as each step completes.
- Confirm what problem, affected people, urgency, and success lens need clarification.
- Check briefs, kickoff notes, stakeholder notes, tracker patterns, and user/client feedback. Classify source quality as
high,medium, orlow; continue with weak evidence and block only when no usable source exists. - Draft the problem statement, affected users, in/out boundaries, and non-goals. Separate source facts from inference.
- Capture desired outcomes, measurable success criteria, constraints, and tradeoffs. Do not invent numeric targets or deadlines.
- Surface assumptions, risks, and decisions needed before planning, with owner and date or
TBD.
What ships with it
2 files 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.
- 12d ago First seen · 69 lines · 40 tokens per session scan A ba68380188f8
pipa-problem-framing is a skill published in the GitHub repository lunchpaillola/pipa-skills (3 stars, last pushed 3d ago), licensed MIT. It adds 40 tokens to every session and 715 once invoked, about $0.0002 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 2026-08-31.
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