Borrowing it
Nothing to install: this file belongs to JRS1986/CodingScaffold. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/JRS1986/CodingScaffold/main/AGENTS.mdgit clone --depth 1 https://github.com/JRS1986/CodingScaffoldWrote 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/instructions/jrs1986/codingscaffold/agents-md)<a href="https://agentmods.dev/instructions/jrs1986/codingscaffold/agents-md"><img src="https://agentmods.dev/badge/instructions/jrs1986/codingscaffold/agents-md/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/instructions/jrs1986/codingscaffold/agents-md"><img src="https://agentmods.dev/badge/instructions/jrs1986/codingscaffold/agents-md.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 | $0.00868 | $0.00868 |
| Opus 5.5 | $0.00347 | $0.00347 |
| Sonnet 5.5 | $0.00174 | $0.00174 |
| Haiku 4.5 | $0.00087 | $0.00087 |
Grade A, and why
CodingScaffold AGENTS.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 1mo 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agents — CodingScaffold
This is the agent-context file for the CodingScaffold project itself. The constraints below apply to any AI coding agent working on this repo.
What this project is
A local-first, deterministic scaffold for AI-assisted coding teams. It is not a coding agent and never calls a model at runtime. Anything an agent contributes here should respect that posture.
Verification commands
Run these before claiming a change is done. Each must pass with exit code 0.
uv run ruff check— lint passes.uv run pytest -q— full test suite passes (330+ tests as of v0.5.0).
For larger changes, also run the scaffold on itself as a smoke check:
coding-scaffold context lint --target .— must pass with no errors.coding-scaffold eval run --target .— must pass.
The repo ships an .coding-scaffold/eval-config.json that disables the checks for
policy_exists and denied_files_configured because this repo deliberately ships no
policy pack and no agent-permissions.json (see "Deliberately absent" below).
Project constraints
- No new runtime dependencies.
pyproject.toml'sdependencies = []is intentional. Dev-only deps go in[project.optional-dependencies].devand must justify their weight. - No LLM calls. The scaffold is deterministic by design; pytest verifies this by running offline. Any feature that wants an LLM is the coding tool's responsibility.
- No network calls. The only allowed subprocess is
git. Adding any other network egress requires an explicit design discussion in the PR. - No telemetry. Ever.
- Backwards compatibility. Every existing CLI command should keep working unless a breaking change is explicitly called out in the PR title and the CHANGELOG.
Commit messages
Plain, descriptive commits. Do not append a Co-Authored-By: Claude ... trailer.
Session traces for bigger changes
For PRs that touch three or more modules, or for any architectural change, start a session trace so reviewers can follow the steps without re-running the agent in their head:
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.
- 1mo ago First seen · 85 lines · 868 tokens per session scan A 6b4d4b1fe8d1
CodingScaffold AGENTS.md is an instructions file published in the GitHub repository JRS1986/CodingScaffold (10 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 868 tokens to every session, about $0.0035 per session on Opus 5.5. 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 instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.