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 infraspecdev/tesseract --skill pm-analysisgit clone --depth 1 https://github.com/infraspecdev/tesseractWrote 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/infraspecdev/tesseract/pm-analysis)<a href="https://agentmods.dev/skills/infraspecdev/tesseract/pm-analysis"><img src="https://agentmods.dev/badge/skills/infraspecdev/tesseract/pm-analysis/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/infraspecdev/tesseract/pm-analysis"><img src="https://agentmods.dev/badge/skills/infraspecdev/tesseract/pm-analysis.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 | $0.00041 | $0.01105 |
| Opus 5.5 | $0.00016 | $0.00442 |
| Sonnet 5.5 | $0.00008 | $0.00221 |
| Haiku 4.5 | $0.00004 | $0.00111 |
Grade A, and why
pm-analysis 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PM Analysis Skill
Thin orchestrator that dispatches the appropriate focused subagent(s) based on mode. Post
pm-restructure-v0, the omnibus shield:product-manager agent has been decomposed; this skill
now routes to:
research-framingmode →shield:research-framerresearch-reviewmode →shield:research-reviewer-narrative+shield:user-impact-clarity(PM1) + ... +shield:business-value-alignment(PM10) +shield:framing-coverage-honored(PM11), dispatched in parallelplan-reviewmode →shield:user-impact-clarity(PM1) + ... +shield:business-value-alignment(PM10), dispatched in parallelstandalonemode → same asplan-review(PM1-PM10 in parallel)
The domain knowledge lives in the focused subagents — this skill only determines the mode, gathers input, and dispatches.
When to Use
- Any workflow that needs a product lens — user impact, prioritization, scope discipline, stakeholder framing
- Called from
researchskill to frame questions before research or review findings after synthesis - Called from
plan-reviewskill to add a PM perspective on plans - Direct invocation for standalone PM analysis on any input (RFC, proposal, research doc)
When NOT to Use
- Pure infrastructure or code reviews with no product decisions — use
shield:reviewinstead - Quick factual lookups that don't need a product perspective
Mode Selection
| Context | Mode |
|---|---|
| Called from research skill before research agents run | research-framing |
| Called from research skill after synthesis | research-review |
| Called from plan-review skill | plan-review |
| Called directly or from any other workflow | standalone (default) |
The calling skill passes the mode explicitly. Standalone is the default when no mode is specified.
Dispatch Workflow
- Determine mode — use the explicit parameter from the calling skill, or default to
standalone. - Gather input material — raw topic (for framing), research doc (for research-review), plan doc (for plan-review), or caller-provided input (for standalone).
- Dispatch the appropriate subagent(s) per the routing table below.
- Return output — pass the subagent output(s) back to the calling workflow unchanged. For multi-subagent dispatches (research-review, plan-review, standalone) the orchestrator returns the merged narrative + scorecard the caller expects.
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 · 84 lines · 41 tokens per session scan A b7b3ec9233b7
pm-analysis is a skill published in the GitHub repository infraspecdev/tesseract (5 stars, last pushed 3mo ago), licensed MIT. It adds 41 tokens to every session and 1,105 once invoked, about $0.0002 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 2026-09-03.
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