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 AndreVianna/aid-methodology --skill aid-testgit clone --depth 1 https://github.com/AndreVianna/aid-methodologyWrote 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/andrevianna/aid-methodology/aid-test)<a href="https://agentmods.dev/skills/andrevianna/aid-methodology/aid-test"><img src="https://agentmods.dev/badge/skills/andrevianna/aid-methodology/aid-test/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/andrevianna/aid-methodology/aid-test"><img src="https://agentmods.dev/badge/skills/andrevianna/aid-methodology/aid-test.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 | $0.00111 | $0.01580 |
| Opus 5 | $0.00056 | $0.00790 |
| Sonnet 5 | $0.00022 | $0.00316 |
| Haiku 4.5 | $0.00011 | $0.00158 |
Grade A, and why
aid-test 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 8d 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Test (run + consolidate, resolve nothing)
/aid-test runs the requested verification and consolidates the results -- it does not
author tests (that is /aid-create-test, a keep-cycle create-family skill). It is
review-shaped: run-a-tool is the evidence-gathering step, and consolidating results into
severity-tagged findings that hand off to /aid-fix is exactly the /aid-review shape --
so this reuses aid-review's machinery (work folder, 7-column ledger, clean-context
verify, present, printed-suggestion handoff). The three test-* kind-siblings
(/aid-test-security, /aid-test-performance, /aid-test-data-quality) delegate here.
- Read-only on the source; never fixes (findings ->
/aid-fix). - Not a numbered pipeline phase; does not route to
/aid-execute.
State machine: INTAKE -> RUN -> VERIFY (loop) -> PRESENT [human] -> HANDOFF? -> DONE.
Print the [State: NAME] -- {purpose} entry line on each state.
State: INTAKE
- Require a target. Empty argument -> ask one bootstrapping question ("What should I test or verify?") and wait.
- Determine the verification kind from the request (or the kind a sibling bound):
functional (unit/integration/e2e), security (SAST/DAST/fuzz/dependency-audit),
performance (workload/threshold/environment), data-quality (schema/freshness/
completeness/uniqueness), or model-eval (run the eval harness, assert metric vs
threshold). The framework is inferred from the KB (
test-landscape.md). - Pick the path: Fast -- a clear target + kind ("run the security scan on the auth module", "benchmark the /orders endpoint vs the p99 SLO") -> run now. Guided -- vague -> scope target / kind / threshold first.
- Classify complexity (model + effort): simple run ->
aid-reviewerat sonnet / medium; deep security/perf analysis -> opus / high. Verifier tier >= producer. - Consult the Work Initiation Gate, then allocate the work folder + STATE. First run
the gate (
.claude/aid/templates/work-initiation-gate.md):bash .claude/aid/scripts/works/enumerate-works.sh(main tree + every git worktree). Empty -> allocate, no prompt. Works exist -> ask new-vs-continuation; on continuation route to the chosen work's resume door and STOP (allocate nothing); on new work: create and enter the worktree per the gate's§ 3astep 2 (worktree-lifecycle.sh create <work-id> <name>, STOP on a non-zero exit or empty path, else enter the resolved path), then allocate (pipeline.path: lite,initiator: aid-test,lifecycle: Running,active_skill: aid-test;phasenot driven).
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.
- 8d ago First seen · 127 lines · 111 tokens per session scan A f3b39a622a7b
aid-test is a skill published in the GitHub repository AndreVianna/aid-methodology (5 stars, last pushed 2d ago), licensed MIT. It adds 111 tokens to every session and 1,580 once invoked, about $0.0006 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 2026-09-03.
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