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 baleen37/bstack --skill verifygit clone --depth 1 https://github.com/baleen37/bstackWrote 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/baleen37/bstack/verify)<a href="https://agentmods.dev/skills/baleen37/bstack/verify"><img src="https://agentmods.dev/badge/skills/baleen37/bstack/verify/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/baleen37/bstack/verify"><img src="https://agentmods.dev/badge/skills/baleen37/bstack/verify.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 | $0.00113 | $0.03129 |
| Opus 5.5 | $0.00045 | $0.01252 |
| Sonnet 5.5 | $0.00023 | $0.00626 |
| Haiku 4.5 | $0.00011 | $0.00313 |
Grade B, and why
verify scanned grade B with 1 finding 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 19d 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.
Enumerates other installed skillsmediumAgent snooping
Other skills' SKILL.md files reveal prompts, capabilities and secrets that should be invisible to peers.
ls .claude/skills/ .agents/skills/ # repo root How it starts
The opening of the file, as written. The whole thing — 274 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Verification is runtime observation. You build the app, run it, drive it to where the changed code executes, and capture what you see. That capture is your evidence. Nothing else is.
Don't run tests. Don't typecheck. Running them here proves you can run CI — not that the change works. Not as a warm-up, not "just to be sure," not as a regression sweep after. The time goes to running the app instead.
Don't import-and-call. import { foo } from './src/...' then
console.log(foo(x)) is a unit test you wrote. The function did what
the function does — you knew that from reading it. The app never ran.
Whatever calls foo in the real codebase ends at a CLI, a socket, or
a window. Go there.
Find the change
The scope is what you're verifying — usually a diff, sometimes just "does X work." In a git repo, establish the full range (a branch may be many commits, or the change may still be uncommitted):
git log --oneline @{u}.. # count commits (if upstream set)
git diff @{u}.. --stat # full range, not HEAD~1
git diff origin/HEAD... --stat # no upstream: committed vs base
git diff HEAD --stat # uncommitted: working tree vs HEAD
gh pr diff # if in a PR context
State the commit count. Large diff truncating? Redirect to a file then read it. Repo but no diff from any of these → say so, stop. No repo → the scope is whatever the user named; ask if they didn't.
The diff is ground truth. Any description is a claim about it. Read both. If they disagree, that's a finding.
Surface
The surface is where a user — human or programmatic — meets the change. That's where you observe.
| Change reaches | Surface | You |
|---|---|---|
| CLI / TUI | terminal | type the command, capture the pane — example |
| Server / API | socket | send the request, capture the response — example |
| GUI | pixels | drive it under xvfb/Playwright or a browser automation tool, screenshot |
| Library | package boundary | sample code through the public export — import pkg, not import ./src/... |
| Prompt / agent config | the agent | run the agent (claude -p, codex exec), capture its behavior |
| CI workflow | Actions | dispatch it, read the run |
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.
- 19d ago Changed · +108 lines · +65 tokens per session scan A → B 5cdead3b000d
- 1mo ago Changed · +8 lines bb4bd743500a
- 1mo ago Changed · -4 lines 4aabc2a0b186
- 1mo ago First seen · 162 lines · 48 tokens per session scan A f14fd3a4f862
verify is a skill published in the GitHub repository baleen37/bstack (4 stars, last pushed 18d ago), licensed MIT. It adds 113 tokens to every session and 3,129 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it B with 1 finding (enumerates other installed skills). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
eval-dataset-design
A guide to creating reliable test sets for AI agents. Each evaluation task includes the request, the simulated user's behaviour, a reset starting state, and a success check that can be independently verified.
tika-eval-compare
Compare extracts from two Tika builds over a corpus to detect regressions in content, encoding, exceptions, and embedded-document handling. Use for "compare before/after extracts", "eval this change against the corpus".
cua-driver
Use Cua Driver for desktop or browser tasks that are awkward or unavailable through Bash/APIs, or when the user explicitly wants GUI interaction: app testing, visual bug reproduction, form filling, calendar entry, screenshots, and demo recording. Also covers Cua setup; not OpenAI Codex Computer Use or web research.
jetson-validate-image
Use after jetson-flash-image to run static BSP checks, on-target smoke/regression tests on a flashed DUT, or both. Not for build or flash steps. Triggers: validate bsp, on-target validation.
atmos-validation
Validate Atmos projects, components, arbitrary JSON Schema inputs, EditorConfig, and GitHub Actions; use affected-file selection and native CI annotations.