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 stepanenkoviktor0110-boop/ai-dev-methodology --skill stack-researchgit clone --depth 1 https://github.com/stepanenkoviktor0110-boop/ai-dev-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/stepanenkoviktor0110-boop/ai-dev-methodology/stack-research)<a href="https://agentmods.dev/skills/stepanenkoviktor0110-boop/ai-dev-methodology/stack-research"><img src="https://agentmods.dev/badge/skills/stepanenkoviktor0110-boop/ai-dev-methodology/stack-research.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 | $0.00076 | $0.01569 |
| Opus 5 | $0.00038 | $0.00785 |
| Sonnet 5 | $0.00015 | $0.00314 |
| Haiku 4.5 | $0.00008 | $0.00157 |
Grade A, and why
stack-research 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.
The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
What ships with it
3 files 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.
- 8d ago First seen · 133 lines · 76 tokens per session scan A 36afa41ce7c8
stack-research is a skill published in the GitHub repository stepanenkoviktor0110-boop/ai-dev-methodology (2 stars, last pushed 14d ago), with no licence file. It adds 76 tokens to every session and 1,569 once invoked, about $0.0004 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
codex-review
A manually triggered review procedure that checks completed code against a frozen specification, decision record, and project rules.
closed-remediation-review
A final, closed-scope check that verifies whether agreed fixes from an earlier adversarial review were applied correctly.
adversarial-review
A process for having several independent reviewers inspect the same project evidence and report possible problems. The main agent then decides which findings are valid against the project's official specifications.
openlore-execute-refactor
Apply a confirmed .openlore/refactor-plan.md with a test gate after each change. Use when asked to execute or continue an OpenLore refactoring plan.
ap-reviewer
L3 independent G2/G5 or roadmap reviewer - checks mission coverage, reality, tests, boundaries, and claim-vs-diff; returns binary SMASH or PASS.
ap-sweeper
L3 executor - SWEEP. Fresh production-readiness sweeper that re-derives mission coverage, inspects the changed neighborhood, checks GATELOG provenance, and returns evidence-backed P0..P3 findings.