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/dasdigitalemomentum/opencode-processing-skills/review-implementationnpx skills add DasDigitaleMomentum/opencode-processing-skills --skill review-implementationgit clone --depth 1 https://github.com/DasDigitaleMomentum/opencode-processing-skillsWrote 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/dasdigitalemomentum/opencode-processing-skills/review-implementation)<a href="https://agentmods.dev/skills/dasdigitalemomentum/opencode-processing-skills/review-implementation"><img src="https://agentmods.dev/badge/skills/dasdigitalemomentum/opencode-processing-skills/review-implementation.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 | $0.00042 | $0.01763 |
| Opus 5 | $0.00021 | $0.00881 |
| Sonnet 5 | $0.00008 | $0.00353 |
| Haiku 4.5 | $0.00004 | $0.00176 |
Grade A, and why
review-implementation 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 — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Review Implementation
This skill provides an independent quality gate for completed implementations executed via execute-work-package.
A fresh reviewer (with no implementation context) evaluates the actual code changes against the plan, acceptance criteria, and coding standards. The review is persisted as a plan artifact.
When to Use
Use this skill when:
- A phase has been implemented via
execute-work-packageand you want to validate before committing/merging. - You want to verify that acceptance criteria are actually met (not just claimed).
- You want an independent assessment of test quality and coverage.
- The user explicitly requests an implementation review.
Do not use this skill to:
- Review the plan itself (use
review-plan). - Review an implementation plan before execution (use
review-implementation-plan). - Fix implementation issues during the independent review pass. After the review is complete, accepted related findings may transition to
review-fixin the same reviewer session.
Review Focus
The primary specifies the review focus when delegating. The default focus is functional and technical findings — correctness, feasibility, completeness of the solution.
Review posture
No Gold-Plating. No Adversarial Reviewing. No Scope Creep. Report only evidence-backed problems that affect correctness, security, acceptance, or the reviewed objective. Do not hunt for gotchas, invent improvements, or keep a review/fix loop alive to create more work. This does not mean overlooking real defects.
Formal criteria (DoD compliance checklists, NFR conformance, reference consistency, documentation cleanup) are secondary. Only include formal findings when they reveal real problems — not as standard checkboxes to fill. A review cluttered with formal nitpicking buries the findings that matter.
The primary passes the focus via {{focus}} in the delegation prompt. If no focus is specified, use the default.
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.
- 4d ago First seen · 158 lines · 42 tokens per session scan A f3a22fe72111
review-implementation is a skill published in the GitHub repository DasDigitaleMomentum/opencode-processing-skills (59 stars, last pushed 24d ago), licensed MIT. It adds 42 tokens to every session and 1,763 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 2026-08-30.
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…