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 skills/darkroomengineering/cc-settings/tldrnpx skills add darkroomengineering/cc-settings --skill tldrgit clone --depth 1 https://github.com/darkroomengineering/cc-settingsWrote 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.
[](https://agentmods.dev/skills/darkroomengineering/cc-settings/tldr)<a href="https://agentmods.dev/skills/darkroomengineering/cc-settings/tldr"><img src="https://agentmods.dev/badge/skills/darkroomengineering/cc-settings/tldr.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00053 | $0.02425 |
| Opus 5 | $0.00026 | $0.01213 |
| Sonnet 5 | $0.00011 | $0.00485 |
| Haiku 4.5 | $0.00005 | $0.00243 |
Grade A, and why
tldr 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 209 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TLDR Code Analysis
Standalone Codex fallback
cc-settings does not install the TLDR MCP into standalone Codex. Ignore the
Claude context, allowed-tools, and requires frontmatter in that host and
keep the task read-only with native tools. Use rg --files to map the tree,
rg -n '<symbol|pattern>' for exact references, direct import searches such as
rg -n 'from .*<module>|require\(.*<module>', and caller searches for the
symbol followed by focused file reads. Use git diff --name-only plus test-name
and import searches for change impact.
Do not invoke or claim to have invoked a TLDR MCP in standalone Codex. Report the native searches actually run and their limitations. The remaining workflow is for Claude hosts with the configured TLDR MCP.
Token-efficient codebase analysis behind the tldr MCP server. It returns the symbols, edges, and slices you asked for instead of whole file bodies, so a question that would cost several full reads costs one small structured answer.
No measured savings figure is published here on purpose. cc-settings carried a "~95% fewer tokens" claim for months with no benchmark behind it anywhere in the repo — the kind of number
AGENTS.mdnow forbids (No savings against a run that never happened). To get a real figure, answer the same question both ways and compare the token counts your own session reports.
The engine is provisioned by cc-settings. The tool names below are the stable contract; only the engine behind them changes. Select with CC_CODE_INTEL_ENGINE.
Default: native-ts — a zero-dependency TypeScript-compiler codemap. TS/JS only. Implements structure, tree, extract, arch, imports, importers, calls, context, impact, change_impact. Everything else returns unsupported-by-native-engine, which means the analysis did not run — fall back to Grep, never report it as an empty finding.
Opt-in: CC_CODE_INTEL_ENGINE=llm-tldr — multi-language, plus semantic, dead, diagnostics, slice, cfg, dfg, search. Use it on Rust/Python/Go repos. Selecting it means re-running setup.sh with the variable set (see Prerequisites), not just exporting it. Two caveats, both measured 2026-07-27:
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.
- 3d ago First seen · 209 lines · 53 tokens per session scan A d6d84fd66970
tldr is a skill published in the GitHub repository darkroomengineering/cc-settings (42 stars, last pushed 5d ago), licensed MIT. It adds 53 tokens to every session and 2,425 once invoked, about $0.0003 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.
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