autonomous-development-workflow

A set of instructions for coding agents working independently without a person supervising each step.

In plain words
What is it for?
Use it when completing a task autonomously, especially when the project has Cursor rules, AGENTS.md or CLAUDE.md files, automated checks, formatting tools, linting, or tests.
Why use it?
It gives the agent a defined process for finding project rules, following the existing workflow, running checks, and preparing changes for review.

Cursor rule for Cursor

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 rules/technickai/claude_telemetry/autonomous-development-workflow
Clone the repo
git clone --depth 1 https://github.com/TechNickAI/claude_telemetry

Made for: Cursor.

Per session 8 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 486 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 $0.00008 $0.00486
Opus 5 $0.00004 $0.00243
Sonnet 5 $0.00002 $0.00097
Haiku 4.5 $0.00001 $0.00049

Measured 2d ago against content hash bd76c1fd5a34, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

autonomous-development-workflow 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.

.cursor/rules/autonomous-development-workflow.mdc · 77 lines

How it starts

The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Autonomous Development Workflow

For AI agents completing tasks without human supervision. The goal: deliver a clean pull request that passes all checks and gets merged without back-and-forth.

Before Implementation

Read all cursor rules in .cursor/rules/. These define the project's standards. Every applicable rule must be followed.

If CLAUDE.md or AGENTS.md exist in the project root, read those for additional context.

Implementation

Write code following all cursor rules. Reference specific rules by reading the files directly.

Validation - Use the Tooling

The project has tooling configured. We use it instead of manually trying to comply.

Check for pre-commit and run if exists:

[ -f .pre-commit-config.yaml ] && pre-commit run --all-files

Read .github/workflows/build.yml (or ci.yml, test.yml) and replicate those validation steps locally, for example:

ruff check --fix .    # Auto-fix linting
ruff format .         # Auto-format code
pytest                # Run tests

If we added functionality, we add tests following project patterns. Aim for 95% coverage - solid testing without obsessing over every edge case.

Only commit and push when all validation passes. Green checks make for happy merges! ✅

Self-Review

Run git diff and review every change, as a senior developer would.

Read through ALL cursor rules again and verify our code follows each applicable guideline.

Would we approve this in code review? If not, keep iterating until it's something we're pleased with.

Submission

Generate commit message following git-commit-message.mdc (if present).

Use gh pr create to submit a high-quality pull request with clear description of what changed and why.

Boundaries

Proceed autonomously: using existing tooling, following established patterns, changes within task scope.

Ask first: major architectural changes, changes that would result in data loss, etc.

Success

A successful autonomous PR means: all automated checks pass, code follows all cursor rules, tests are green, and the developer merges it without requesting changes. Use the tooling to get there - it's our friend! 🎉

Read the full file on GitHub · 77 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. 2d ago First seen · 77 lines · 8 tokens per session scan A bd76c1fd5a34

Subscribe to this mod's changes

autonomous-development-workflow is a cursor rule published in the GitHub repository TechNickAI/claude_telemetry (30 stars, last pushed 10mo ago), licensed MIT. It adds 8 tokens to every session and 486 once invoked, about $0.0000 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.