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/arcblock/agent-skills/blocklet-prnpx skills add ArcBlock/agent-skills --skill blocklet-prgit clone --depth 1 https://github.com/ArcBlock/agent-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/arcblock/agent-skills/blocklet-pr)<a href="https://agentmods.dev/skills/arcblock/agent-skills/blocklet-pr"><img src="https://agentmods.dev/badge/skills/arcblock/agent-skills/blocklet-pr.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 | $0.00054 | $0.04105 |
| Opus 5 | $0.00027 | $0.02053 |
| Sonnet 5 | $0.00011 | $0.00821 |
| Haiku 4.5 | $0.00005 | $0.00411 |
Grade A, and why
blocklet-pr 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 — 605 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Blocklet PR
Help developers create standardized Pull Requests for blocklet projects, ensuring code quality and following project PR templates.
Core Philosophy
"Quality gates + standardized workflow."
PRs are not submitted casually. Before submission, code must pass lint and tests, must be on a working branch (never directly on main branch), and PR content must follow project templates. Enforced standardization reduces human oversight errors.
Prerequisites
- Current directory is a blocklet project (contains
blocklet.yml) - Has code changes to commit
Reference Files
Branch conventions and repository info are read from local reference files (in blocklet-url-analyzer skill directory):
blocklet-url-analyzer/references/org-arcblock-repos.md- ArcBlock repos (core infrastructure, SDKs, mobile apps)blocklet-url-analyzer/references/org-blocklet-repos.md- Blocklet repos (blocklet applications, kits, tools)blocklet-url-analyzer/references/org-aigne-repos.md- AIGNE repos (AI agent framework, LLM adapters)
Active Loading Policy (ALP)
Load reference files on-demand based on repository organization. Do not preload all files.
| Trigger Condition | Load File |
|---|---|
| Repository in ArcBlock org | blocklet-url-analyzer/references/org-arcblock-repos.md |
| Repository in blocklet org | blocklet-url-analyzer/references/org-blocklet-repos.md |
| Repository in AIGNE-io org | blocklet-url-analyzer/references/org-aigne-repos.md |
| Uncertain which organization | First read blocklet-url-analyzer/references/README.md |
Loading Strategy:
- Determine repository organization from
git remote get-url origin - Load only the reference file for that organization
- If organization unknown, read README.md first for high-density summary
Workflow
Execute the following phases in order.
Phase 1: Workspace Check
Refer to blocklet-branch skill for branch operations.
Skill location: blocklet-branch/SKILL.md
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 · 605 lines · 54 tokens per session scan A fe319bfa9352
blocklet-pr is a skill published in the GitHub repository ArcBlock/agent-skills (5 stars, last pushed 3d ago), licensed MIT. It adds 54 tokens to every session and 4,105 once invoked, about $0.0003 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…