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 InSciCo/i-framework --skill classifygit 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/classify)<a href="https://agentmods.dev/skills/inscico/i-framework/classify"><img src="https://agentmods.dev/badge/skills/inscico/i-framework/classify/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/inscico/i-framework/classify"><img src="https://agentmods.dev/badge/skills/inscico/i-framework/classify.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 | $0.00062 | $0.00899 |
| Opus 5.5 | $0.00025 | $0.00360 |
| Sonnet 5.5 | $0.00012 | $0.00180 |
| Haiku 4.5 | $0.00006 | $0.00090 |
Grade A, and why
classify 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 — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/classify — rank features innovation vs. implementation
You judge each feature against the UVP and assign a binary bucket plus a 0–100 weight, then produce the ranked "where's our edge" index and flag portfolio problems.
Reference: the rubric
A feature is innovation if it embodies the unfair advantage — a reason a user switches. It is implementation if it is necessary for a usable product but undifferentiated (table-stakes every competitor has).
- Decision test: "If a competitor shipped this exact feature tomorrow, would we lose our edge?" Yes → innovation. "Would every competitor have this too?" Yes → implementation.
- Weight: implementation →
0. Innovation →1–100, proportional to how much of the moat the feature carries. Reserve 80–100 for the few features that are the reason to exist. - Trace: every innovation feature must cite a
contributes_to: UVP-xfromProduct/innovation.md. A feature that traces to no UVP element is probably implementation — reclassify it.
Procedure
-
Load the reference. Read
Product/innovation.mdfor the enumerated UVP elements (UVP-1, UVP-2…). If it's missing, warn that classification is being done without a defined UVP (soft) and proceed using the user's stated differentiators. Also readProduct/competition.mdif present — the comparison matrix is hard evidence: a capability every rival already has is table-stakes (implementation); a whitespace capability mapping to a UVP is innovation. Prefer matrix evidence over gut. -
Target. Default to all
Product/Features/F*.md; or a single feature if the user names one. -
Classify each. Apply the decision test, set
classification,innovation_weight,contributes_to, and a one-sentenceclassification_rationale. Update the file frontmatter in place (don't touch the body). -
Portfolio sanity checks — report, don't silently pass. Use concrete thresholds so the check is consistent, not a vibe:
- No innovation features (0%) → red flag: "nothing here is a reason to exist." Push the user to find the edge or revisit
/innovate. - Innovation-heavy (>40% of features tagged innovation) → warn: most products are mostly table-stakes; challenge the weakest "innovation" tags. (>60% is a hard flag.)
- Weight clustering — only checked when there are ≥3 innovation features (with fewer, spread isn't meaningful — skip it). When it applies: if innovation weights span <30 points (e.g. all in 80–100), the weights aren't ranking anything; push for spread.
- Near-duplicate edge (two+ innovation features tracing to the same UVP with overlapping
depends_on) → likely one capability split in two; suggest merging, or making one a child of the other viadepends_on. - Healthy shape: mostly implementation (≤40% innovation), a few sharp innovation features with a real weight gradient.
- No innovation features (0%) → red flag: "nothing here is a reason to exist." Push the user to find the edge or revisit
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 · 52 lines · 62 tokens per session scan A 3e4c9d1623e2
classify is a skill published in the GitHub repository InSciCo/i-framework (4 stars, last pushed 3mo ago), licensed MIT. It adds 62 tokens to every session and 899 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 2026-08-31.
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