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/inscico/i-framework/product-statusnpx skills add InSciCo/i-framework --skill product-statusgit clone --depth 1 https://github.com/InSciCo/i-frameworkWrote 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/inscico/i-framework/product-status)<a href="https://agentmods.dev/skills/inscico/i-framework/product-status"><img src="https://agentmods.dev/badge/skills/inscico/i-framework/product-status.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 5.1 | $0.00066 | $0.00615 |
| Opus 5 | $0.00033 | $0.00308 |
| Sonnet 5 | $0.00013 | $0.00123 |
| Haiku 4.5 | $0.00007 | $0.00061 |
Grade A, and why
product-status 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 5d 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 — 32 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/product-status — the dashboard (read-only)
You summarize the whole Product/ folder at a glance. Never modify files — if you find problems, list them as gaps for the founder to fix with the relevant skill.
Procedure
-
Read everything. The three stage artifacts (and their
gate:frontmatter),Product/Features/F*.md(frontmatter + body),Product/features-index.mdif present, andProduct/competition.mdif present. -
Compute:
- Stage/gate completion — which of the three gates are passed vs. open (the risk-burndown line).
- Feature counts — total, by
classification, bypriority(MoSCoW), bystatus. - Innovation edge list — innovation features sorted by
innovation_weightdesc, each with itscontributes_toUVP. - Weight distribution — are weights spread or clustered?
-
Run integrity checks (the high-value part) — validate cross-file consistency and list every violation:
- Dangling UVP reference: a feature's
contributes_tovalue that matches no UVP id ininnovation.md. - UVP orphan: a UVP element in
innovation.mdwith no innovation feature tracing to it. - Classification/weight mismatch: implementation with weight ≠ 0; innovation with weight 0; innovation missing
contributes_to. - Thin feature: missing a user-story clause, or <3 acceptance criteria.
- Broken dependency: a
depends_onid that points to no existing feature. - Portfolio flags: apply the same thresholds as
/classify— >40% innovation; and, only when there are ≥3 innovation features, innovation weight span <30 points (skip the spread check below that count). - Cherry-picked matrix: if
competition.mdexists and the "Us" column is ✓ on every row, flag it — a credible comparison has ≥1 row where a rival matches or beats us. - Unverified competitor claims: if
competition.mdexists, count cells marked?and surface them as items to verify (with the snapshot date).
- Dangling UVP reference: a feature's
-
Render a concise dashboard — a risk-burndown header, a counts table, the ranked edge list, and a clearly separated Gaps / next actions section that names which skill fixes each gap (
/feature,/classify,/innovate).
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.
- 5d ago First seen · 32 lines · 66 tokens per session scan A 1ea96e160410
product-status is a skill published in the GitHub repository InSciCo/i-framework (4 stars, last pushed 1mo ago), licensed MIT. It adds 66 tokens to every session and 615 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.
Other skills, from other repositories
product-brainstorming
Brainstorm product ideas, explore problem spaces, and challenge assumptions as a thinking partner. Use when exploring an opportunity, generating solutions, or stress-testing an idea before converging on a direction.
pr
Comprehensive PR/issue review - analyzes architecture, tests, identifies unrelated changes mixed in, drafts review comment or issue comment. Use when user asks to review a PR, check a PR, look at PR changes, or comment on an issue.
backlog
Read, work, and maintain a Git repo's deferred-work items in docs/backlog/, one file per item. Use when the user says "backlog", "check backlog", "what's on my backlog", "work the backlog", "address the backlog", "add to backlog", "clean up backlog", or when a review or task produced items that are real but not being…
ask-codex
Consult OpenAI Codex for investigation, debugging, or code review. Use when user explicitly asks to "ask codex", "check with codex", "codex review", or as a last resort when stuck after 4+ failed attempts at debugging, investigation, or bug fix and completely out of ideas. Codex is slow (2-5 min), so only escalate…
clarify
This skill should be used when user appears confused, frustrated, or shows misalignment between expectations and reality. Triggers on phrases like "I don't understand", "this doesn't make sense", "confused", "wait, shouldn't it...", "why is this happening", "I thought X did Y", contradictory statements, or frustration…
writing-style
Use for technical communication - GitHub/GitLab tickets, PR/MR descriptions, issue comments, code review comments, commit messages. Direct, brief style with no AI-speak. NOT for README.md, public docs, or blog posts.