long-running-agents

long-running-agents is a cursor rule for Cursor from sijeeshmiziha/visionagent. It costs 421 tokens per session, scanned A, original, MIT.

A set of rules for agents that work on software tasks across multiple sessions.

In plain words
What is it for?
Use it to organize long-running coding work with a feature list, progress file, focused sessions, and descriptive commits.
Why use it?
It prevents unfinished work from becoming difficult to resume by requiring incremental changes, progress records, feature tracking, and clean handoffs.

Cursor rule for Cursor

Written for Cursor: installed under .cursor/.

Good fit Use it to organize long-running coding work with a feature list, progress…

Compare 6 cursor rules from other repositories ↓
Install with agentmods
npx agentmods add rules/sijeeshmiziha/visionagent/long-running-agents
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.

Clone the repo
git clone --depth 1 https://github.com/sijeeshmiziha/visionagent

Made for: Cursor.

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.

agentmods badge for long-running-agents

README.md
[![agentmods](https://agentmods.dev/badge/rules/sijeeshmiziha/visionagent/long-running-agents.svg)](https://agentmods.dev/rules/sijeeshmiziha/visionagent/long-running-agents)
Your own site
<a href="https://agentmods.dev/rules/sijeeshmiziha/visionagent/long-running-agents"><img src="https://agentmods.dev/badge/rules/sijeeshmiziha/visionagent/long-running-agents.svg" alt="Measured on agentmods" height="20"></a>
Per session 421 This file is loaded in full into every session.
When invoked 421 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00421 $0.00421
Opus 5 $0.00211 $0.00211
Sonnet 5 $0.00084 $0.00084
Haiku 4.5 $0.00042 $0.00042

Measured 6d ago against content hash 325039adcadb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

long-running-agents 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 6d 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/long-running-agents.mdc · 40 lines

What it actually says

Long-Running Agent Harness

Two-Agent Pattern

  • Initializer agent (first run): Set up the environment—feature list (JSON), init script (e.g. init.sh), progress file (e.g. *-progress.txt), and an initial git commit.
  • Coding agent (every subsequent run): Make incremental progress only; leave structured updates (git commit + progress file) so the next session can resume.

Incremental Progress

  • Work on one feature at a time. Never attempt to one-shot complex tasks; this leads to half-implemented, undocumented work when context resets.
  • Choose the next feature from the feature list; do not skip or batch unrelated work.

Progress and Clean State

  • Maintain a structured progress file (e.g. *-progress.txt or JSON) and write descriptive git commits at the end of each session.
  • End every session with clean state: code that could be merged to main—no major bugs, orderly and well-documented. Use git to revert bad changes if needed.

Feature List

  • Use structured JSON (not Markdown) for feature tracking with pass/fail status.
  • Do not remove or edit feature definitions; only update the passes (or equivalent) field. Removing tests leads to missing or buggy functionality.

Getting Up to Speed

At the start of each new session:

  1. Run pwd; read progress file and git log to understand recent work.
  2. Read the feature list and pick the highest-priority incomplete feature.
  3. Run init script / dev server and run a basic smoke test before implementing anything new. Fix existing bugs first.

End-to-End Testing

  • Verify features as a user would (e.g. browser automation for web apps).
  • Only mark a feature as passing after careful testing. Do not mark features done without proper verification.
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. 6d ago First seen · 40 lines · 421 tokens per session scan A 325039adcadb

Subscribe to this mod's changes

long-running-agents is a cursor rule published in the GitHub repository sijeeshmiziha/visionagent (2 stars, last pushed 5mo ago), licensed MIT. It adds 421 tokens to every session, about $0.0021 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.