Current thesis
Use `radar.md` for the live thesis, changed thesis, and open questions that deserve attention now.
Python CLI · Markdown repo
Track agent signals in plain Markdown
Record what changed across coding agents, workflows, field evidence, and storage infrastructure — without a database, crawler, or web UI.
$ python scripts/agent_radar.py brief
CORE FILES
-
radar.md -
agent-watchlist.md -
user-field-notes.md -
playbook.md -
storage-angle.md
BRIEF 3 watchlist updates · 2 field notes · 1 storage signal
Markdown-first · stdlib CLIdaily append · weekly synthesis
Markdown-first radar
Signals you can edit and version
Agent Radar keeps thesis, watchlist, field notes, playbooks, and storage implications in plain Markdown files — plus a stdlib Python CLI to scaffold, validate, and brief the repo.
Core Markdown files
A simple structure for high-signal tracking
Each file has a clear job. Daily and weekly folders append signals; automation and cloud-agent workflows keep the cadence without turning the repo into a platform.
- 01
Thesis
`radar.md` holds current thesis, changed thesis, and open questions.
- 02
Watchlist
`agent-watchlist.md` tracks mainstream and emerging agents with evidence labels.
- 03
Field notes
`user-field-notes.md` and `playbook.md` capture real workflows and reusable patterns.
- 04
Storage angle
`storage-angle.md` records workspace, sandbox, artifact, log, and replay implications.
In the terminal
In the terminal
Agent watchlist
Track mainstream and emerging agents in `agent-watchlist.md` — product moves, not launch hype.
Real user evidence
Capture workflows, complaints, tricks, and failure cases in `user-field-notes.md` with source discipline.
Reusable playbooks
Promote patterns that generalize beyond one incident into `playbook.md` — prompts, setup tricks, recovery paths.
FAQ
What is Agent Radar not?
Not a news dump, crawler framework, vector store, or complex knowledge base. It is a lightweight editable Markdown structure with a small Python CLI.
How does the CLI work?
Python 3.10+ and only the standard library. `init`, `daily`, `weekly`, `monthly`, `status`, `validate`, and `brief` scaffold and check the repo from any subdirectory.
Can it run on a schedule?
Yes. GitHub Actions workflows support scheduled cloud-agent runs with source lanes, scoring, telemetry, and bilingual report output.
What about private sources?
Authorized logged-in or private signals may inform the radar, but public output must be anonymized and public-safe. See `docs/maintenance.md` and `SECURITY.md`.