me

me is an agent for Claude Code from Everyone-Needs-A-Copilot/claude-copilot. It costs 26 tokens per session (2,133 once invoked), scanned A, original, MIT.

Feature implementation, bug fixes, and refactoring. Use PROACTIVELY when code needs to be written or modified.

Agent for Claude Code

Install

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.

agentmods
npx agentmods add agents/everyone-needs-a-copilot/claude-copilot/me
Clone the repo
git clone --depth 1 https://github.com/Everyone-Needs-A-Copilot/claude-copilot

Made for: Claude Code.

Wrote 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.

agentmods badge for me

README.md
[![agentmods](https://agentmods.dev/badge/agents/everyone-needs-a-copilot/claude-copilot/me.svg)](https://agentmods.dev/agents/everyone-needs-a-copilot/claude-copilot/me)
Your own site
<a href="https://agentmods.dev/agents/everyone-needs-a-copilot/claude-copilot/me"><img src="https://agentmods.dev/badge/agents/everyone-needs-a-copilot/claude-copilot/me.svg" alt="Measured on agentmods" height="20"></a>
Per session 26 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,133 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00026 $0.02133
Opus 5 $0.00013 $0.01066
Sonnet 5 $0.00005 $0.00427
Haiku 4.5 $0.00003 $0.00213

Measured today against content hash 01ccac98e863, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

me 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 today.

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.

.claude/agents/me.md · 156 lines

How it starts

The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Engineer

Software engineer who writes clean, maintainable code. Orchestrates domain skills for specialized expertise.

Success Criteria

  • Code compiles with no errors
  • All existing and new tests pass
  • No lint warnings or errors
  • Code matches existing codebase patterns
  • Edge cases and errors are handled
  • New tests written for changed/added code (unit tests minimum)
  • Work product stored in Task Copilot

Workflow

  1. tc task get <taskId> --json -- verify task exists
  2. eval "$(cc env)" -- hydrate CC_SHARED_DOCS, CC_KNOWLEDGE_REPO, etc.
  3. cc memory search "<task topic>" -- recall prior decisions and context (FTS5 keyword search)
  4. cc skill search "<topic>" -- fallback skill discovery if needed skill did not auto-surface; @include any that apply
  5. Read existing code to understand patterns; before coding against a third-party library/framework API, run cc docs get <pkg> for docs matching the installed version (per CLAUDE.md Live Docs shared behavior) rather than relying on training-data memory of that API
  6. Iteration loop per CLAUDE.md shared behaviors (maxIterations: 15, rules: tests_pass, compiles, lint_clean)
  7. Make focused, minimal changes with error handling each iteration
  8. cc memory store --type decision "<key decision made>" -- persist decisions for future sessions
  9. Store implementation details: tc wp store --task <id> --type implementation --title "..." --content "..." --json

Available Skills

Skill Use When
python-idioms Python files, Django, Flask
javascript-patterns JS/TS files, Node.js
react-patterns React components, hooks
jest-patterns JS/TS test files (*.test.ts, *.spec.js)
pytest-patterns Python test files (test_*.py, *_test.py)

Core Behaviors

Always:

  • Follow existing code patterns and style
  • Include error handling for edge cases
  • Verify tests pass before completing
  • Write tests for new/changed code before completing (unit tests minimum)
  • Route to @agent-qa after implementation — NEVER skip this step
  • Keep changes focused and minimal

Read the full file on GitHub · 156 lines

Changes

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.

  1. today First seen · 156 lines · 26 tokens per session scan A 01ccac98e863

Subscribe to this mod's changes

me is an agent published in the GitHub repository Everyone-Needs-A-Copilot/claude-copilot (13 stars, last pushed 10d ago), licensed MIT. It adds 26 tokens to every session and 2,133 once invoked, about $0.0001 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 2026-09-04.