What is autosprint CLAUDE.md?

Project instructions for Autosprint, an automated loop that plans work, implements a task, runs Python tests, and commits changes in a target repository. They also define its language, structure, and safety boundaries.

Use them when running or modifying Autosprint, preparing sprint tasks, checking its commands, or contributing to its Python code.

They help an agent follow Autosprint’s process and avoid changing the Autosprint tool itself instead of its target project.

How haakonbull/autosprint configures Claude Code

Reuse

Borrowing it

Nothing to install: this file belongs to haakonbull/autosprint. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/haakonbull/autosprint/master/CLAUDE.md

Clone the repo

git clone --depth 1 https://github.com/haakonbull/autosprint

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.

README.md

[![agentmods](https://agentmods.dev/badge/instructions/haakonbull/autosprint/claude-md/github.svg)](https://agentmods.dev/instructions/haakonbull/autosprint/claude-md)

Your own site

<a href="https://agentmods.dev/instructions/haakonbull/autosprint/claude-md"><img src="https://agentmods.dev/badge/instructions/haakonbull/autosprint/claude-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.

Your own site · 80×15

<a href="https://agentmods.dev/instructions/haakonbull/autosprint/claude-md"><img src="https://agentmods.dev/badge/instructions/haakonbull/autosprint/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 2,142 This file is loaded in full into every session.

When invoked 2,142 The same file — it is already loaded in full.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

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.

Model	Per session	Once invoked
Fable 5.1	$0.02142	$0.02142
Opus 5	$0.01071	$0.01071
Sonnet 5	$0.00428	$0.00428
Haiku 4.5	$0.00214	$0.00214

Measured 10d ago against content hash b135cb8f9588, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

autosprint 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 10d 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.

CLAUDE.md · 139 lines

How it starts

The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Autosprint

Automated sprint loop — Plan, Implement, Test, Commit — powered by the Claude Agent SDK and GitHub Copilot SDK.

Language

All tool output, code, comments, commit messages, and user-facing documentation are English only.

What this project does

Autosprint runs a PIT loop against a target repository. Each sprint:

Plan — one or more AI agents propose tasks, a selector merges them into autosprint/plan.md
Implement — an AI agent implements the top pending task
Test — pytest runs the target repo's test suite (Python, not LLM)
Commit — if tests pass, changes are committed to the branch

Autosprint never modifies itself. The orchestrator refuses to run if TARGET_REPO points at the autosprint repo. All file changes happen inside the target repository; autosprint contains only methodology, prompts, and orchestration.

Project structure

src/autosprint/
  orchestrator.py   # pit_loop, commit_sprint, plan_only, main — the PIT loop itself
  cli.py            # argparse, prepare(), one-shot subcommands, stop control
  init.py           # `autosprint init` + config wizard + prepare-step seed/check helpers
  how_far.py        # `autosprint how-far` — read-only distance-to-destination report
  plan_phase.py     # Plan phase: prompts, team-lead context, update_plan, replan
  implement_phase.py # Implement phase: dispatch, refusal-fallback, failure logs
  test_phase.py     # Test phase: drives the test runner, revert/commit decision, self-test
  test_runners.py   # TestRunner adapters — normalizes test execution per language (pytest + vitest)
  run_log.py        # sprint-outcomes log, plan-decisions log, runtime stats, escalation
  banners.py        # Section banners, PIT-loop tree, start banner, show-config print
  git_ops.py        # git, git_restore, git_commit, summarise_working_tree_diff
  parsing.py        # Result-block parsing for agent responses
  paths.py          # Path/filename constants for autosprint/* layout
  agents.py         # Individual agent definitions (name, model, system_prompt, tools) + AGENTS registry
  teams.py          # TEAM_* dicts + TEAMS registry (composes agents into planning rosters)
  dispatch.py       # query_agent / query_agents — SDK dispatch, caching, parallelism
  config.py         # Environment-driven settings via pydantic-settings
  plan.py           # plan.md parser/writer, Plan/PendingTask/CompletedTask, group_titles
  db.py             # SQLite mirror of sprint outcomes
  output.py         # printlev() — level-gated stdout
  errors.py         # add_context, RevertReason, PhaseFailedError, StopRequested, WaypointReached
.claude/agents/
  plan-agent.md            # Prompt template for a single agent's Plan phase (code projects)
  plan-team.md             # Prompt for the selector when merging team proposals (code projects)
  plan-agent-research.md   # Plan-phase prompt for research-team members (sources / paper / deep-dives)
  plan-team-research.md    # Selector prompt for the research team lead
  implement.md             # Prompt for the Implement phase (artifact-agnostic — code or research)
tests/
  test_plan_phase.py
  test_implement.py
  test_pit_loop.py
  test_plan.py

Read the full file on GitHub · 139 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.

10d ago First seen · 139 lines · 2,142 tokens per session scan A b135cb8f9588

Subscribe to this mod's changes

autosprint CLAUDE.md is an instructions file published in the GitHub repository haakonbull/autosprint (5 stars, last pushed 2mo ago), licensed MIT. It adds 2,142 tokens to every session, about $0.0107 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 2026-08-31.

Planning

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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).

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autosprint: Instructions file for Claude Code