agentmods.dev

CodeStory copilot-instructions.md

Repository instructions for using CodeStory to answer questions about a codebase. CodeStory is a repository-grounding tool that helps an agent understand project code before making claims or planning changes.

In plain words
What is it for?
Use it before explaining source code, planning edits, selecting tests, or reviewing changes in this repository; if unavailable, inspect the source directly.
Why use it?
It reduces guesses about the source code and helps choose relevant edits and tests based on the repository's actual structure.

Instructions file for GitHub Copilot

37 2d ago A scan 139 tokens original Apache-2.0
View the source file TheGreenCedar/CodeStory
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/thegreencedar/codestory/copilot-instructions
Clone the repo
git clone --depth 1 https://github.com/TheGreenCedar/CodeStory

Made for: GitHub Copilot.

Per session 139 This file is loaded in full into every session.
When invoked 139 The same file — it is already loaded in full.
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 $0.00139 $0.00139
Opus 5 $0.00069 $0.00069
Sonnet 5 $0.00028 $0.00028
Haiku 4.5 $0.00014 $0.00014

Measured 2d ago against content hash 657ffb1a7323, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

CodeStory copilot-instructions.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 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.

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.

.github/copilot-instructions.md · 11 lines

What it actually says

CodeStory Grounding

Use CodeStory proactively for repository questions. Do not wait for the user to mention it by name.

Before making source claims, planning edits, choosing tests, or reviewing changes in this repository:

  1. Call the CodeStory tool that matches the task and pass the repository's absolute root as project.
  2. If it reports preparing or updating, retry that same tool after its reported delay. Do not poll status.
  3. Use status or codestory://status only to diagnose a failed or unexpectedly slow call.
  4. If MCP is missing, inspect source normally and report that CodeStory was unavailable for the task.
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. 2d ago First seen · 11 lines · 139 tokens per session scan A 657ffb1a7323

Subscribe to this mod's changes

CodeStory copilot-instructions.md is an instructions file published in the GitHub repository TheGreenCedar/CodeStory (37 stars, last pushed 2d ago), licensed Apache-2.0. It adds 139 tokens to every session, about $0.0007 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 2026-08-30.

Data and AIResearchTestingai-agentscode-graphcode-intelligencecode-searchknowledge-graphllm-context
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