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 story-coveragegit 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/story-coverage)<a href="https://agentmods.dev/skills/infraspecdev/tesseract/story-coverage"><img src="https://agentmods.dev/badge/skills/infraspecdev/tesseract/story-coverage/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/story-coverage"><img src="https://agentmods.dev/badge/skills/infraspecdev/tesseract/story-coverage.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 | $0.00068 | $0.01204 |
| Opus 5.5 | $0.00027 | $0.00482 |
| Sonnet 5.5 | $0.00014 | $0.00241 |
| Haiku 4.5 | $0.00007 | $0.00120 |
Grade A, and why
story-coverage 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Story Coverage
Derive expected user stories from personas + goals + feature domain. Cross-reference NFR/GTM/rollout sections for orphan references.
When to Use
shield:agile-coachcalls this skill while grading dim 4 eval points 4f and 4g of a PRD/prdcommand (Phase B) calls this skill between PRD Sections 6 (Goals) and 8 (Stories) to scaffold expected stories
Input contract
The caller provides:
personas: list of {id, name, description, goals}goals: list of {id, description}feature_domain: best-effort domain hint (e.g., "auth", "payment", "content", "internal-tool", "infrastructure")existing_sections: optional — content of NFR / GTM / Rollout / Risks sections (for orphan-reference detection)
Output contract
Return a list of expected stories with structured metadata:
{
"expected_stories": [
{
"rationale": "persona-goal" | "archetype" | "orphan-reference",
"persona_id": "P1",
"goal_id": "G1",
"archetype": "password-reset",
"story_title": "Anika resets her password",
"story_template": { ... },
"severity": "P0" | "P1" | "P2"
}
]
}
Derivation rules
Rule 1 — Persona × Goal cross-product
For each (persona, goal) pair, derive at minimum:
- Happy path story — the persona achieves the goal successfully
- One named error/recovery path — what happens when the happy path fails (timeout, partial failure, user abandons)
If 0 stories address a (persona, goal) pair → flag P0 ("persona P's goal G has no story").
If exactly 1 story (happy path only) → flag P1 ("persona P's goal G has happy path but no error/recovery").
Rule 2 — Archetype match
Look up the feature domain in archetypes.md. If the domain matches one of: auth, payment, content, lifecycle, multi-region, billing, observability, retrieve its archetypal flow list.
For each archetypal flow that's NOT covered by an existing story → flag P1 or P2 based on the archetype's marked severity in archetypes.md.
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.
- 1mo ago First seen · 119 lines · 68 tokens per session scan A b34918cba5a9
story-coverage is a skill published in the GitHub repository infraspecdev/tesseract (5 stars, last pushed 3mo ago), licensed MIT. It adds 68 tokens to every session and 1,204 once invoked, about $0.0003 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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