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 agentmods add skills/hellothisworld/agent-skill-verification-template/codebase-understandingnpx skills add HelloThisWorld/agent-skill-verification-template --skill codebase-understandinggit clone --depth 1 https://github.com/HelloThisWorld/agent-skill-verification-templateWhat 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 | $0.00041 | $0.00552 |
| Opus 5 | $0.00020 | $0.00276 |
| Sonnet 5 | $0.00008 | $0.00110 |
| Haiku 4.5 | $0.00004 | $0.00055 |
Grade A, and why
codebase-understanding 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 yesterday.
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 — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codebase Understanding
A Claude-style skill that answers natural-language questions about a codebase and
backs every claim with file:line evidence. It is designed to be verified
like a production component — see skill-contract.json for
the machine-readable contract and verification-rules.md
for how outputs are graded.
When to use
Use this skill to answer questions such as "Which component publishes
UserCreatedEvent?" or "Which file handles payment authorization?" against a known
repository (here, the fixture repo under fixtures/sample-repo).
Tools
| Tool | Purpose |
|---|---|
repo_search |
Case-insensitive substring search. Returns {file, line, text} matches. |
read_file |
Read a file by repo-relative path to confirm evidence. |
Contract rule: repo_search must be used before read_file.
Procedure
- Identify the key symbols/keywords in the question.
- Use
repo_searchto locate candidate evidence. - Use
read_fileto confirm the strongest candidate. - Produce a structured answer where every claim cites a real
file:line. - If the evidence is missing or ambiguous, return
insufficient_evidencewith an emptyclaimsarray. Never invent an answer or a citation.
Output contract
The skill must return JSON with:
status:answered|insufficient_evidence|refusedanswer: a short natural-language answerclaims: array of{ text, citations: [{ file, line }] }toolCalls: array of{ tool, arguments }confidence(optional):low|medium|high
See examples.md for concrete input/output pairs.
Design note: contract vs. model
This SKILL.md and the contract are model-independent — they describe what a
correct answer looks like. How reliably a given model satisfies the contract
(pass rate, latency, cost, failure modes) is measured separately by the eval
harness and will differ per model. The offline mock adapter is a reference
implementation that satisfies the contract deterministically.
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.
- yesterday First seen · 61 lines · 41 tokens per session scan A f6281f37d4e7
codebase-understanding is a skill published in the GitHub repository HelloThisWorld/agent-skill-verification-template (1 stars, last pushed 9d ago), licensed MIT. It adds 41 tokens to every session and 552 once invoked, about $0.0002 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
install-loop
Install Loop Engineering into a project via the unified CLI front door (@cobusgreyling/loop). Prefer this over invoking loop-init / loop-audit separately. Week-one is report-only; never enable auto-merge or unattended fixes unless the human explicitly asks and doctor is healthy.
pr-review-triage
Watch open PRs, check CI status, review staleness, merge conflicts, and unanswered review comments. Produces a prioritized watchlist.
loop-verifier
Independent verification agent for loop-produced changes. Finds reasons to reject. Runs tests. Confirms diff scope. Use after minimal-fix or any implementer sub-agent — never in the same role as the implementer.
dependency-triage
Scan package manifests and lockfiles for outdated and vulnerable dependencies. Classify by severity and update type.
issue-triage
Scan open issues and discussions, deduplicate, prioritize, and propose labels. Provides a clean actionable queue.
draft-release-notes
Turn changelog-scan output into polished, categorized release notes draft. Propose only.