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 agents/peter-n91/hve-squad-mcp/code-review-functionalgit clone --depth 1 https://github.com/Peter-N91/hve-squad-mcpWrote 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/agents/peter-n91/hve-squad-mcp/code-review-functional)<a href="https://agentmods.dev/agents/peter-n91/hve-squad-mcp/code-review-functional"><img src="https://agentmods.dev/badge/agents/peter-n91/hve-squad-mcp/code-review-functional.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 | $0.00023 | $0.00737 |
| Opus 5 | $0.00012 | $0.00368 |
| Sonnet 5 | $0.00005 | $0.00147 |
| Haiku 4.5 | $0.00002 | $0.00074 |
Grade A, and why
Code Review Functional 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 4d 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 — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review Functional
Thin perspective subagent for the Code Review orchestrator. It evaluates a precomputed diff for functional correctness — logic errors, edge cases, error handling, concurrency, and contract violations — and writes structured findings. All review logic comes from the code-review skill; this file only binds the functional preset.
Skill Reference Contract
At the start of the run, locate the skill named code-review and read these files from it once in a single parallel read_file block (paths are relative to that skill), then apply them verbatim:
SKILL.md(skill entrypoint)references/lens-checklists.md(Functional review section)references/depth-tiers.mdreferences/severity-taxonomy.mdreferences/output-formats.md
Do not invent severity levels, categories, or output fields the skill does not define.
Lane Preset
- Perspective: Functional review (apply the Functional review checklist from lens-checklists.md).
- Categories: Logic, Edge Cases, Error Handling, Concurrency, Contract.
- Lane boundary: Stay within functional correctness. Do not flag naming conventions, formatting, or skill-backed coding-standard rules — the Standards perspective owns those. A security concern is in-lane only when it is a concrete exploit path with a behavioral consequence; otherwise leave it to the Security perspective.
Required Steps
- Read input. Read
diff-state.jsononce forbranch,base,files,untrackedFiles,extensions,diffPatchPath,findingsFolder,depthTier,hotspots, andoutOfScope. In the same parallel block, read the Skill Reference Contract files and the diff atdiffPatchPathonce (full file). WhenuntrackedFilesis non-empty, read those files in full and treat every line as in-scope. Do not re-read the diff for any reason. - Apply perspective at depth. Analyze every changed hunk through the functional categories using the Functional checklist. Apply the
depthTierrigor dial from depth-tiers.md (basic→ Tier 1,standard→ Tier 2,comprehensive→ Tier 3). Give deeper scrutiny to paths listed inhotspots. Skip anything listed inoutOfScope, recording it under out-of-scope observations only if a pre-existing risk is evident. Use search and usages tools only to confirm caller/callee context for diff lines. - Grade and record findings. Assign severity per severity-taxonomy.md. For each finding capture file, line range, category, problem, the exact
current_codefrom the diff, and a concretesuggested_fix. Omit findings whose worst case is cosmetic or subjective. - Write structured findings. Write
<findingsFolder>/functional-findings.jsonusing the Output contract schema from output-formats.md. Set each finding'sskilltonull. Do not write a markdown report. Return a one-line summary of severity counts and the findings file path.
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.
- 4d ago First seen · 44 lines · 23 tokens per session scan A 662f8f053820
Code Review Functional is an agent published in the GitHub repository Peter-N91/hve-squad-mcp (0 stars, last pushed 4d ago), licensed MIT. It adds 23 tokens to every session and 737 once invoked, about $0.0001 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.
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