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 skills add mayank-io/mstack --skill surface-usage-patternsgit clone --depth 1 https://github.com/mayank-io/mstackWrote 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/mayank-io/mstack/surface-usage-patterns)<a href="https://agentmods.dev/skills/mayank-io/mstack/surface-usage-patterns"><img src="https://agentmods.dev/badge/skills/mayank-io/mstack/surface-usage-patterns/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mayank-io/mstack/surface-usage-patterns"><img src="https://agentmods.dev/badge/skills/mayank-io/mstack/surface-usage-patterns.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00067 | $0.00916 |
| Opus 5.5 | $0.00027 | $0.00366 |
| Sonnet 5.5 | $0.00013 | $0.00183 |
| Haiku 4.5 | $0.00007 | $0.00092 |
Grade A, and why
surface-usage-patterns 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 2mo 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.
Reads agent configuration directorieslowAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
find ~/.claude/projects -name "*.jsonl" -type f 2>/dev/null | head -100 Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
How it starts
The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Surface Usage Patterns
Analyze all Claude Code sessions on this computer to identify usage patterns and improvement opportunities.
Step 1: Gather Session Data
Scan all Claude Code session data. Sessions are stored in ~/.claude/projects/ as JSONL files.
# Find all session directories and conversation files
find ~/.claude/projects -name "*.jsonl" -type f 2>/dev/null | head -100
Also check for:
~/.claude/for any global configuration and history- Project-level
.claude/directories for project-specific patterns
Read a representative sample of recent sessions (at least 10-20) to understand what the user does across projects.
Step 2: Analyze Usage Patterns
For each session, extract:
- What task was performed (bug fix, feature, refactor, research, DevOps, etc.)
- Which tools were used most (Bash, Read, Edit, Write, Agent, WebSearch, etc.)
- Which skills/commands were invoked (
/commit,/review-pr, custom skills, etc.) - Repetitive multi-step workflows (sequences of actions that recur across sessions)
- Common pain points (retries, corrections, clarifications that suggest friction)
- Projects worked on and their domains
Step 3: Produce the Report
Present a structured breakdown with the following sections:
Most Frequent Activities
Rank the top activities by frequency. Include:
- Category (e.g., "Code review", "Feature implementation", "Debugging")
- Approximate frequency (daily, weekly, occasional)
- Typical workflow steps involved
Candidates for Skills
Identify workflows that should become reusable skills. A good skill candidate:
- Is a multi-step workflow that repeats across sessions or projects
- Has a consistent pattern but isn't currently codified
- Would benefit from documented best practices and guardrails
For each candidate, provide:
- Name: Suggested skill name (kebab-case)
- Trigger: When this skill should activate
- Current workflow: What the user does today (steps)
- Improvement: What the skill would standardize or automate
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.
- 2mo ago First seen · 101 lines · 67 tokens per session scan A 9217ccaee69e
surface-usage-patterns is a skill published in the GitHub repository mayank-io/mstack (6 stars, last pushed 3d ago), licensed MIT. It adds 67 tokens to every session and 916 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
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.
component-fixtures
Use when creating or updating component fixtures for screenshot testing or their shared infrastructure, or when designing UI components to be fixture-friendly. Covers fixture file structure, theming, service setup, CSS scoping, async rendering, validation, and common pitfalls.