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/joinwell52-ai/codeflowmu-open/pm-solve-problemsnpx skills add joinwell52-AI/CodeFlowMu-open --skill pm-solve-problemsgit clone --depth 1 https://github.com/joinwell52-AI/CodeFlowMu-openWrote 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/joinwell52-ai/codeflowmu-open/pm-solve-problems)<a href="https://agentmods.dev/skills/joinwell52-ai/codeflowmu-open/pm-solve-problems"><img src="https://agentmods.dev/badge/skills/joinwell52-ai/codeflowmu-open/pm-solve-problems.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 | $0.00052 | $0.00552 |
| Opus 5 | $0.00026 | $0.00276 |
| Sonnet 5 | $0.00010 | $0.00110 |
| Haiku 4.5 | $0.00005 | $0.00055 |
Grade A, and why
pm-solve-problems 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 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.
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 — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PM Problem Solving
Own the reasoning even when execution belongs to another role. Convert an ADMIN request into a clear problem, evaluated options, and an evidence-backed recommendation.
Workflow
- Restate the outcome in operational terms. Separate the requested result from a proposed implementation.
- Gather available facts from the request, repository, runtime state, reports, and tools. Label unknowns explicitly.
- Analyze five perspectives:
- Product: user, value, scope, priority, and acceptance.
- Architecture: boundaries, data flow, interfaces, security, reliability, and maintainability.
- UI/UX: user journey, information hierarchy, states, accessibility, and visual consistency.
- Delivery: dependencies, milestones, risks, rollback, and verification.
- Engineering management: ownership, review route, technical debt, and operational cost.
- Identify the root problem and constraints. Do not confuse symptoms with causes.
- Generate at least two viable options for non-trivial decisions. Include the option to preserve the current design when appropriate.
- Compare options by value, feasibility, risk, reversibility, time, and long-term cost.
- Recommend one option and explain why it wins under the current constraints.
- Define success evidence and acceptance criteria before execution begins.
- Delegate implementation only after the solution is coherent. Keep responsibility for synthesis and final quality.
- Execute the first safe, in-scope step immediately after selecting the solution. Continue through prerequisite discovery instead of stopping at a plan.
Output Contract
- Problem and desired outcome
- Verified facts and explicit unknowns
- Constraints and affected users/systems
- Options with trade-offs
- Recommended solution and rationale
- Risks and mitigations
- Acceptance criteria and evidence plan
Guardrails
- Do not ask ADMIN questions that repository inspection or safe research can answer.
- Do not present a single unexplored idea as a decision.
- Do not invent evidence, certainty, costs, or implementation behavior.
- Do not delegate the act of understanding the problem.
- Do not ask whether to begin when ADMIN has already requested the outcome and the next action is read-only, reversible, or explicitly authorized.
- Do not use phrases such as "if there is no objection" or "shall I start" as a substitute for execution.
- Ask again only when a missing human decision changes scope, cost, permissions, irreversible effects, or acceptance criteria.
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.
- 4d ago First seen · 47 lines · 52 tokens per session scan A 9654ec503f39
pm-solve-problems is a skill published in the GitHub repository joinwell52-AI/CodeFlowMu-open (2 stars, last pushed 10d ago), licensed MIT. It adds 52 tokens to every session and 552 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 2026-08-31.
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