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/youglin-dev/aha-loop/researchnpx skills add YougLin-dev/Aha-Loop --skill researchgit clone --depth 1 https://github.com/YougLin-dev/Aha-LoopWhat 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 | $0.00039 | $0.02055 |
| Opus 5 | $0.00019 | $0.01027 |
| Sonnet 5 | $0.00008 | $0.00411 |
| Haiku 4.5 | $0.00004 | $0.00205 |
Grade A, and why
research scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s "https://crates.io/api/v1/crates/tokio" | jq '.crate.max_stable_version' How it starts
The opening of the file, as written. The whole thing — 340 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Research Skill
Conduct thorough technical research before implementation to ensure high-quality, informed decisions.
Workspace Mode Note
When running in workspace mode, all paths are relative to .aha-loop/ directory:
- Research reports:
.aha-loop/research/(notscripts/aha-loop/research/) - Knowledge base:
.aha-loop/knowledge/(notknowledge/) - Vendor directory:
.aha-loop/.vendor/(not.vendor/)
The orchestrator will provide the actual paths in the prompt context.
The Job
- Identify research topics from the current story's
researchTopicsfield - Fetch third-party library source code if needed
- Search documentation and best practices
- Analyze and compare alternatives
- Generate a research report
- Update knowledge base with findings
- Mark
researchCompleted: truein prd.json
Research Process
Step 1: Identify What to Research
Read the current story from prd.json and extract:
researchTopics- explicit topics to investigate- Dependencies mentioned in acceptance criteria
- Patterns referenced in the description
Also check:
- Previous story's
learningsfield for follow-up research needs knowledge/project/gotchas.mdfor related known issues
Step 2: Fetch Library Source Code (If Needed)
For any third-party library research, fetch the source:
# Fetch specific library
./scripts/aha-loop/fetch-source.sh rust tokio 1.35.0
# Or fetch all project dependencies
./scripts/aha-loop/fetch-source.sh --from-deps
After fetching, the source will be at .vendor/<ecosystem>/<name>-<version>/
Library Version Selection
Always Prefer Latest Stable Versions
When researching or recommending libraries, always check for and prefer the latest stable version unless there's a specific compatibility reason not to.
Version Research Process
-
Query the package registry for latest version:
# Rust (crates.io) curl -s "https://crates.io/api/v1/crates/tokio" | jq '.crate.max_stable_version' # Or use cargo cargo search tokio --limit 1 # Node.js (npm) npm view react version # Python (PyPI) pip index versions requests 2>/dev/null | head -1
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 · 340 lines · 39 tokens per session scan A 550a49da6e61
research is a skill published in the GitHub repository YougLin-dev/Aha-Loop (181 stars, last pushed 7mo ago), licensed MIT. It adds 39 tokens to every session and 2,055 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). 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…