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/luisfelipemoro/harness-devkit/improve-codebase-architecturenpx skills add LuisFelipeMoro/Harness-devkit --skill improve-codebase-architecturegit clone --depth 1 https://github.com/LuisFelipeMoro/Harness-devkitWhat 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 | $0.00084 | $0.00489 |
| Opus 5 | $0.00042 | $0.00244 |
| Sonnet 5 | $0.00017 | $0.00098 |
| Haiku 4.5 | $0.00008 | $0.00049 |
Grade A, and why
improve-codebase-architecture 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 3d 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.
What it actually says
Report findings only — never fix in this skill. Each finding includes severity, location, and a concrete recommendation.
Refactor guard: this skill only reports. Any refactor that follows must be protected by a characterization test first — pin the current observable behaviour with a passing test (it goes RED the moment the refactor changes behaviour), then refactor under green. Never restructure code that has no test covering it; add the test first.
Phase 1 — Map (1 Explore sub-agent, model: haiku)
Input: Working directory. Optionally: focus area. Output: Raw observations list. Boundary: no analysis, no recommendations.
Dispatch one read-only Explore sub-agent using the call template in references/arch-report-reference.md.
Phase 2 — Score
Input: Phase 1 observations. Output: Findings grouped by severity.
| Severity | Examples |
|---|---|
| Critical | Domain logic in HTTP/DB layer; circular imports; unhandled errors on mutation path |
| High | 3+ callers duplicating logic; file >500 lines; cross-feature deep imports |
| Medium | File 300–500 lines; inconsistent patterns; magic values |
| Low | Naming inconsistency; minor duplication; dead code |
Phase 3 — Report
Write HTML report to /tmp/arch-report-<YYYY-MM-DD>.html.
See references/arch-report-reference.md for HTML scaffold.
Print: Architecture report: /tmp/arch-report-<date>.html — N critical, N high, N medium, N low findings.
Phase 4 — Grill (optional)
Offer: "Want to stress-test any finding? Type /grill-me with the finding."
Phase 5 — ADR (optional)
For each Critical/High finding the user wants to address: offer docs/adr/ADR-NNN-title.md.
See references/arch-report-reference.md for the ADR template.
What ships with it
1 file 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.
- 3d ago First seen · 44 lines · 84 tokens per session scan A 6f898ad29722
improve-codebase-architecture is a skill published in the GitHub repository LuisFelipeMoro/Harness-devkit (10 stars, last pushed 3d ago), licensed MIT. It adds 84 tokens to every session and 489 once invoked, about $0.0004 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…