agentshare CLAUDE.md

Repository instructions for Claude Code, an AI coding assistant. They describe how to plan larger tasks, delegate focused work, record lessons after corrections, and verify changes before finishing.

In plain words
What is it for?
They are for planning multi-step tasks, using subagents for research or parallel analysis, updating a lessons file, reviewing relevant lessons, and running tests or comparisons before completion.
Why use it?
They give the coding assistant a repeatable way to handle complex work and reduce skipped planning, repeated mistakes, and untested changes.

Instructions file

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 instructions/devashar13/agentshare/claude-md
Clone the repo
git clone --depth 1 https://github.com/devashar13/agentshare
Per session 563 This file is loaded in full into every session.
When invoked 563 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin 91% copy Near-identical to another mod 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 $0.00563 $0.00563
Opus 5 $0.00282 $0.00282
Sonnet 5 $0.00113 $0.00113
Haiku 4.5 $0.00056 $0.00056

Measured yesterday against content hash 2ad671e073de, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agentshare CLAUDE.md 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 yesterday.

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.

Origin

This is a copy

91% identical to OpenAIWorkshop copilot-instructions.md — 107 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

CLAUDE.md · 57 lines

How it starts

The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Workflow Orchestration

1. Plan Mode Default

  • Enter plan mode for ANY non-trivial task (3+ steps or architectural decisions)
  • If something goes sideways, STOP and re-plan immediately – don't keep pushing
  • Use plan mode for verification steps, not just building
  • Write detailed specs upfront to reduce ambiguity

2. Subagent Strategy

  • Use subagents liberally to keep main context window clean
  • Offload research, exploration, and parallel analysis to subagents
  • For complex problems, throw more compute at it via subagents
  • One task per subagent for focused execution

3. Self-Improvement Loop

  • After ANY correction from the user: update tasks/lessons.md with the pattern
  • Write rules for yourself that prevent the same mistake
  • Ruthlessly iterate on these lessons until mistake rate drops
  • Review lessons at session start for relevant project

4. Verification Before Done

  • Never mark a task complete without proving it works
  • Diff behavior between main and your changes when relevant
  • Ask yourself: "Would a staff engineer approve this?"
  • Run tests, check logs, demonstrate correctness

5. Demand Elegance (Balanced)

  • For non-trivial changes: pause and ask "is there a more elegant way?"
  • If a fix feels hacky: "Knowing everything I know now, implement the elegant solution"
  • Skip this for simple, obvious fixes – don't over-engineer
  • Challenge your own work before presenting it

6. Autonomous Bug Fixing

  • When given a bug report: just fix it. Don't ask for hand-holding
  • Point at logs, errors, failing tests – then resolve them
  • Zero context switching required from the user
  • Go fix failing CI tests without being told how

Task Management

  1. Plan First: Write plan to tasks/todo.md with checkable items
  2. Verify Plan: Check in before starting implementation
  3. Track Progress: Mark items complete as you go
  4. Explain Changes: High-level summary at each step
  5. Document Results: Add review section to tasks/todo.md
  6. Capture Lessons: Update tasks/lessons.md after corrections

Read the full file on GitHub · 57 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. yesterday First seen · 57 lines · 563 tokens per session scan A 2ad671e073de

Subscribe to this mod's changes

agentshare CLAUDE.md is an instructions file published in the GitHub repository devashar13/agentshare (2 stars, last pushed 6mo ago), licensed MIT. It adds 563 tokens to every session, about $0.0028 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to OpenAIWorkshop copilot-instructions.md, differing in 107 lines, and is treated as a copy.

Related

Other instructions, from other repositories