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.
npx agentmods add instructions/fedroraddict/rango/agents-mdgit clone --depth 1 https://github.com/fedroraddict/rangoWhat 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 | $0.00984 | $0.00984 |
| Opus 5 | $0.00492 | $0.00492 |
| Sonnet 5 | $0.00197 | $0.00197 |
| Haiku 4.5 | $0.00098 | $0.00098 |
Grade A, and why
rango 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 yesterday.
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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rango workspace notes
Rango = the AI copilot layer for the Chameleon Ultra: ai_shell/ (Python wrapper
library) + plugin/ (Kimi Code plugin). The upstream Chameleon Ultra CLI is not
vendored — scripts/install-cli.sh fetches it (git clone, codeload tarball fallback);
at runtime it is located via $CHAMELEON_SOFTWARE/script,
../ChameleonUltra/software/script, then ~/Workspace/chameleonUltra/software/script
(see ai_shell/bridge.py).
Layout
ai_shell/— bridge (in-processexec_cmd+ stdout/stderr capture),ops.py(state snapshot, slot picking, verified card-load sequence),library.py(host card library),dictionaries.py(key dicts),analyze.py(offline dump analyzer, Flipper.nfcinput, known-system key fingerprints, SAK/NTAG type ID), Kimi client, enhanced REPL,selfcheck.py+test_analyze.py.plugin/— Kimi Code plugin (manifest + MCP server + skill +agents/card-analyst.md). Install with/plugins install <this repo>/pluginthen/reload; reinstall after edits (installs are copied to~/.kimi-code/plugins/managed/). The MCP server runs on this repo's.venvviaplugin/run-mcp.sh, which locates the repo via$RANGO_ROOT→plugin/.rango-root(written byscripts/setup-plugin.sh) → in-place layout →~/Workspace/rango,~/rango.scripts/—install-cli.sh(upstream CLI fetcher),setup-plugin.sh(writesplugin/.rango-root; re-run it if the repo moves, then reinstall the plugin).adapters/— per-harness config/snippets for running the MCP server, skill, and card-analyst agent from Claude Code, Codex CLI, and OpenCode (the plugin manifest is Kimi-specific; the MCP server is not)..github/workflows/ci.yml— CI: ruff, tests, selfcheck (fetches the upstream CLI viascripts/install-cli.shon the runner).
Verify changes
uv run ruff check ai_shell/ plugin/mcp/
uv run python -m ai_shell.selfcheck # cited commands exist upstream + gate semantics + slot-pick guards + simulated /plugins install boot
uv run python -m ai_shell.test_analyze # dump-analyzer regression tests
echo -e "hw version\nexit" | uv run python -m ai_shell # offline smoke test
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.
- yesterday First seen · 66 lines · 984 tokens per session scan A ac6f9f18c99c
rango AGENTS.md is an instructions file published in the GitHub repository fedroraddict/rango (0 stars, last pushed 9d ago), licensed MIT. It adds 984 tokens to every session, about $0.0049 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.
Other instructions, from other repositories
kimi-responses-adapter AGENTS.md
AGENTS.md instructions for jianyun8023/kimi-responses-adapter, covering repository guidelines, project structure & module organization, build, test, and development commands, coding style & naming conventions and testing guidelines.
apm python.instructions.md
Python development guidelines.
codemap CLAUDE.md
Instructions for JordanCoin/codemap, covering 🛑 stop — run codemap before any task, repo root requirement (critical) and required usage.
OpenMicro AGENTS.md
Instructions for stephenleo/OpenMicro, covering openmicro — project conventions and releases.
squarebox CLAUDE.md
Instructions for SquareWaveSystems/squarebox, covering claude.md, agent skills, issue tracker, triage labels and domain docs.
domain-experts CLAUDE.md
Instructions for wonsukchoi/domain-experts, covering domain experts — session bootstrap, non-negotiables when adding or editing roles, dual-graph context policy, mandatory: always follow this order and token usage.