Latitude is an open-source platform for monitoring AI agents by collecting execution traces, grouping failures, dispatching coding agents to make fixes, and replaying failures to verify them. Teams use it to observe agent behavior, investigate errors, and monitor whether fixes prevent regressions. The catalogue entries include skills, instructions, and an MCP server for working with Latitude.
Borrowing it
Nothing to install: this file belongs to latitude-dev/latitude-llm. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/latitude-dev/latitude-llm/development/.agents/skills/docs/SKILL.mdgit clone --depth 1 https://github.com/latitude-dev/latitude-llmWrote 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/latitude-dev/latitude-llm/docs)<a href="https://agentmods.dev/skills/latitude-dev/latitude-llm/docs"><img src="https://agentmods.dev/badge/skills/latitude-dev/latitude-llm/docs/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/latitude-dev/latitude-llm/docs"><img src="https://agentmods.dev/badge/skills/latitude-dev/latitude-llm/docs.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00079 | $0.02180 |
| Opus 5.5 | $0.00032 | $0.00872 |
| Sonnet 5.5 | $0.00016 | $0.00436 |
| Haiku 4.5 | $0.00008 | $0.00218 |
Grade A, and why
docs 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 1mo 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 — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Documentation Sync
Purpose
Use this skill to keep durable repository knowledge in sync with the current coding session.
The sources of truth are:
- the current conversation
- the current git changes
- the existing
dev-docs/*.md, relevantspecs/*.md, andAGENTS.md
This skill is for durable knowledge, not changelog prose.
Repository docs and specs
dev-docs/contains precise and exhaustive Markdown documentation for each domain or system (top-level*.mdfiles).docs/holds the Mintlify product docs site (docs.json, topical folders such asgetting-started/andtelemetry/, plusimages/,logo/, favicons).- Each domain doc file should cover how the domain or system is architected, built, designed, and structured.
- Keep domain docs organized by domain/system (for example:
dev-docs/reliability.md,dev-docs/evaluations.md,dev-docs/annotations.md,dev-docs/scores.md,dev-docs/issues.md,dev-docs/simulations.md,dev-docs/organizations.md,dev-docs/projects.md,dev-docs/users.md,dev-docs/settings.md,dev-docs/spans.md). specs/is a temporary folder used while a feature or system is under construction.- Each spec or PRD in
specs/should have its own Markdown file and usually include a task list to track progress. - Specs define exactly what, how, and why to build while the feature is under construction, so temporary overlap with docs is acceptable.
- Docs should describe the intended final system after all planned phases are complete, including post-MVP phases, precisely enough to remain authoritative after the corresponding spec is deleted.
- Docs should not be written as a snapshot of the repository's currently implemented state.
- If some part of the final design is still not fully specified, docs may say that the exact detail is still pending precise definition, but they should still be framed around the final intended system.
- When working on a spec, proactively ask clarifying questions and challenge assumptions, gaps, ambiguities, and trade-offs as needed to build the best possible spec.
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.
- 1mo ago First seen · 215 lines · 79 tokens per session scan A 229986b4fcbe
docs is a skill published in the GitHub repository latitude-dev/latitude-llm (4,734 stars, last pushed yesterday), licensed MIT. It adds 79 tokens to every session and 2,180 once invoked, about $0.0003 per session on Opus 5.5. 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.
Other skills, from other repositories
trulens-evaluation-setup
Configure feedback functions and selectors for TruLens evaluations.
trulens-instrumentation
Instrument LLM apps with TruLens OTEL-based tracing - from setup to debugging and optimization.
trulens-notebook-execution
Execute and display Jupyter notebooks for TruLens demos and quickstarts.
trulens-evaluation-workflow
Systematically evaluate your LLM application with TruLens.
trulens-blocking-guardrails
Configure and use feedback functions as runtime blocking guardrails.
trulens-dataset-curation
Create and curate evaluation datasets with ground truth for TruLens.