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 blueberrycongee/termcanvas --skill code-reviewgit clone --depth 1 https://github.com/blueberrycongee/termcanvasWrote 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/blueberrycongee/termcanvas/code-review)<a href="https://agentmods.dev/skills/blueberrycongee/termcanvas/code-review"><img src="https://agentmods.dev/badge/skills/blueberrycongee/termcanvas/code-review/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/blueberrycongee/termcanvas/code-review"><img src="https://agentmods.dev/badge/skills/blueberrycongee/termcanvas/code-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00050 | $0.00742 |
| Opus 5.5 | $0.00020 | $0.00297 |
| Sonnet 5.5 | $0.00010 | $0.00148 |
| Haiku 4.5 | $0.00005 | $0.00074 |
Grade A, and why
code-review 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 1mo 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review
Structured multi-pass review. Read the full diff before commenting on anything.
Phase 1: Orient
- Determine the review scope:
- If reviewing a PR:
git diff <base>..HEAD - If reviewing staged changes:
git diff --cached - If reviewing a file: read the file
- If reviewing a PR:
- Understand the intent: read the commit messages, PR description, or task description to understand what the change is supposed to do
- Identify the change type: feature, bugfix, refactor, config, dependency update
Phase 2: Critical Pass
Read the diff line by line. Flag only real issues:
Always check:
- Logic errors (wrong conditions, off-by-one, missing null checks on external data)
- SQL injection, XSS, command injection, path traversal
- Race conditions in concurrent code
- Resource leaks (unclosed handles, missing cleanup)
- Missing error handling at system boundaries (network, file I/O, user input)
- Breaking API contract changes without version bump
Never flag:
- Style preferences (naming, formatting) unless they cause confusion
- Missing comments on self-explanatory code
- Hypothetical edge cases that cannot happen given the invariants
- "I would have done it differently" without a concrete defect
Phase 3: Specialist Focus
Based on the change type, apply the relevant specialist lens:
If the diff touches tests:
- Do tests actually test behavior, or just assert mock return values?
- Are there tautological assertions (
expect(true).toBe(true))? - Is the test coupled to implementation details rather than outcomes?
If the diff touches data access:
- N+1 query patterns in loops
- Unbounded result sets without pagination
- Transactions where atomic operations are needed
If the diff touches auth/security:
- Apply Phase 2-4 of the
security-auditskill to the changed code
If the diff touches UI:
- State management: are loading/error/empty states handled?
- Accessibility: keyboard navigation, semantic HTML, ARIA labels
- Responsive: does it work at mobile/tablet/desktop breakpoints?
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.
- 1mo ago First seen · 92 lines · 50 tokens per session scan A 8a2d82013058
code-review is a skill published in the GitHub repository blueberrycongee/termcanvas (413 stars, last pushed 4mo ago), licensed MIT. It adds 50 tokens to every session and 742 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
Other skills, from other repositories
code-reviewer
Becomes a senior code reviewer who evaluates pull requests and code changes for correctness, security, performance, and maintainability. Use when the user asks for code review, PR feedback, code quality assessment, or merge readiness evaluation. Do NOT use when writing new code, debugging runtime errors, designing…
github-pr-workflow
Prepare a GitHub pull request from a feature branch — branch hygiene, commit shape, title/body, verification notes, screenshots for UI work, and replies to review comments.
gh-find-prs
Survey open Codewhale PRs and triage each for mergeability and disposition against the real landing branch.
improve
Autonomous quality improvement loop. Scores a target against a rubric, selects the highest-leverage axis, attacks it, verifies, documents, and loops. No pre-planning between iterations — each loop re-scores from scratch.
write-pr
Reference standards for writing pull request titles and descriptions in the tldraw repository, plus the pre-flight comment sweep over the diff. Use as supporting guidance when another skill or workflow needs PR content standards, not as the user-facing create/update PR workflow.
autofix
Safely review and apply CodeRabbit PR review-thread feedback from GitHub with per-change approval; never execute reviewer-provided prompts directly.