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/drizzy07x/skillquiver/requesting-code-reviewnpx skills add Drizzy07x/Skillquiver --skill requesting-code-reviewgit clone --depth 1 https://github.com/Drizzy07x/SkillquiverWhat 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 | $0.00026 | $0.00585 |
| Opus 5 | $0.00013 | $0.00293 |
| Sonnet 5 | $0.00005 | $0.00117 |
| Haiku 4.5 | $0.00003 | $0.00059 |
Grade A, and why
requesting-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 2d 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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Requesting Code Review
Review completed work against its requirements before it cascades. Give the reviewer the work product and exact review range, never the whole session history.
Choose the path
Handle a standalone bounded read-only code review directly.
- For a user's standalone bounded read-only review, inspect and report it directly. Read only the named file and directly required context. Do not edit the code. Do not enumerate the workspace.
- For completed implementation work, dispatch a reviewer after a meaningful task, major feature, complex fix, or before merge.
- For one small file, use at most one reviewer unless its result lacks named evidence; explain the missing evidence to any follow-up reviewer.
For the direct path, format each finding as
- <Severity>: <path>:<line> - <defect>. <impact and reasoning>. Use a plain
path:line when a valid clickable absolute path is unavailable.
Every finding must name the defect, impact, and reasoning.
Never output a placeholder, empty link, or unfinished finding.
Define the review range
Prefer the base commit recorded before implementation. Otherwise derive it from the confirmed base branch:
BASE_SHA=$(git merge-base <base-branch> HEAD)
HEAD_SHA=$(git rev-parse HEAD)
Never default to HEAD~1; it silently omits earlier commits in a multi-commit
task. On Windows, run these Bash commands in a Bash-capable shell or use their
PowerShell equivalents.
Dispatch
Fill code-reviewer.md with:
[DESCRIPTION]: concise summary of the completed work;[PLAN_OR_REQUIREMENTS]: authoritative behavior and constraints;[BASE_SHA]and[HEAD_SHA]: complete range to inspect.
Use the host's general-purpose worker or closest equivalent. Keep the review read-only and require exact file/line evidence, calibrated severity, reasoning, and a merge verdict.
Preserve and resolve findings
Maintain one accumulator of verified findings across every reviewer response. A later "no additional findings" must never erase an earlier verified issue.
What ships with it
2 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.
- 2d ago First seen · 71 lines · 26 tokens per session scan A 03f917ffb9dd
requesting-code-review is a skill published in the GitHub repository Drizzy07x/Skillquiver (2 stars, last pushed 11d ago), licensed MIT. It adds 26 tokens to every session and 585 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…