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.
git clone --depth 1 https://github.com/mathiasbourgoin/rosterWrote 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/commands/mathiasbourgoin/roster/roster-spec-infer)<a href="https://agentmods.dev/commands/mathiasbourgoin/roster/roster-spec-infer"><img src="https://agentmods.dev/badge/commands/mathiasbourgoin/roster/roster-spec-infer/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/commands/mathiasbourgoin/roster/roster-spec-infer"><img src="https://agentmods.dev/badge/commands/mathiasbourgoin/roster/roster-spec-infer.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 | $0.00027 | $0.02872 |
| Opus 5.5 | $0.00011 | $0.01149 |
| Sonnet 5.5 | $0.00005 | $0.00574 |
| Haiku 4.5 | $0.00003 | $0.00287 |
Grade A, and why
roster-spec-infer 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 — 283 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Roster Spec-Infer
Reverse-engineer an evidence-tiered spec from an existing codebase. This is a
read-only analysis skill — it never modifies the target project. Every claim is
labeled by evidence strength: [E1] (test-proven), [E2] (code-inferred),
[E3] (doc-only). Conflicts between code and documentation are surfaced, never
silently resolved.
Input Contract
Required: <target> — a project root directory path (e.g. . or /path/to/project).
- If a file path is given: halt with "Target must be a directory (project root). Got:
<path>." - Slug derivation: lowercase the target directory's basename, replace spaces with
-, strip all non-alphanumeric/hyphen characters. Example:My Project!→my-project. - Collision check: if
specs/<slug>-inferred.mdalready exists, halt with: "Inferred spec already exists for<slug>. Overwrite? [y/N]" — stop if not confirmed.
Tunables:
| Tunable | Default | Effect |
|---|---|---|
include_git_history |
true |
Run Sub-agent 4 (Git History Miner) |
conflict_policy |
surface |
Only supported value: always surface conflicts, never auto-resolve. Reserved for future extension. |
gap_threshold |
0 |
Register every uncovered public symbol as a GAP |
Steps
Sub-agent 1: Test Miner
Spawn a sub-agent (fresh context) with this prompt:
You are a Test Miner. Analyze the test suite of the target project and extract
behavioral assertions as evidence-tier-1 (E1) claims in Given/When/Then format.
Step 1 — Detect test framework (in this priority order):
- package.json `scripts.test` field
- pytest.ini / setup.cfg / pyproject.toml [tool.pytest]
- go.mod (go test ./...)
- pom.xml / build.gradle (mvn test / gradle test)
If no framework detected: emit "No test suite detected — all surfaces are E2/E3 or GAP."
and produce zero E1 claims. Stop.
Step 2 — Run the canonical test command. If exit code is non-zero: halt with:
"Test suite failed — E1 claims cannot be emitted. Fix test failures before
running roster-spec-infer."
Step 3 — Parse passing test files. For each behavioral assertion, produce one
E1 entry in Given/When/Then format:
- [E1] Given <setup/precondition>, When <action or call>, Then <assertion/outcome>
(evidence: <test-file>:<line>)
Use the actual test setup code as "Given", the call under test as "When", and
the assertion as "Then". If a test has multiple assertions, emit one E1 entry
per distinct behavioral claim, not per assertion line.
Cap at top-50 most-covered files if context limits are reached; note:
"Analysis limited to top N files due to context constraints."
Target directory: <target>
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 Changed · -2 lines · -55 tokens per session 26b7db9b8f5c
- 1mo ago First seen · 285 lines · 82 tokens per session scan A 67d7d4516563
roster-spec-infer is a command published in the GitHub repository mathiasbourgoin/roster (2 stars, last pushed 2d ago), licensed MIT. It adds 27 tokens to every session and 2,872 once invoked, about $0.0001 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 2026-09-07.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.