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/toolchain-commands/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/toolchain-commands)<a href="https://agentmods.dev/skills/latitude-dev/latitude-llm/toolchain-commands"><img src="https://agentmods.dev/badge/skills/latitude-dev/latitude-llm/toolchain-commands/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/toolchain-commands"><img src="https://agentmods.dev/badge/skills/latitude-dev/latitude-llm/toolchain-commands.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 3 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 92 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Tool Misuse · line 98 Tool defaults are unsafe or overly permissive (e.g. disabled TLS verification, no authentication, world-writable permissions). Unsafe defaults widen the attack surface.Fix: Override unsafe defaults with secure settings (verify=True, auth required, restrictive permissions). Review and harden all tool configurations.
- medium Privilege Escalation · line 108 Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.Fix: Avoid sudo/root unless strictly required. Prefer least-privilege patterns. If elevation is needed, document the justification and scope.
- medium Privilege Escalation · line 109 Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.Fix: Avoid sudo/root unless strictly required. Prefer least-privilege patterns. If elevation is needed, document the justification and scope.
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 | $0.00046 | $0.01551 |
| Opus 5 | $0.00023 | $0.00776 |
| Sonnet 5 | $0.00009 | $0.00310 |
| Haiku 4.5 | $0.00005 | $0.00155 |
Grade B, and why
toolchain-commands scanned grade B with 2 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 9d 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
sudo dockerd &>/dev/null & # if the daemon is not already running Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| Web | 3000 | `curl http://localhost:3000` (redirect to `/login`) | How it starts
The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Toolchain, commands, and CI
When to use: Installing dependencies, running dev/build/test/lint, filtering packages, single-test runs, git hooks, preparing a clone (.env.development / .env.test), or Docker-backed local services and dev servers.
Stack (summary)
- Runtime: Node.js
25viamise.toml(alsoenginesin rootpackage.json). Usemise install/mise execso Vitest andUint8Array.fromHex/toHexmatch production; Node 22 lacks those APIs and will fail tests that touch@repo/utilscrypto helpers. - Package manager:
package.jsonpackageManagerfield (e.g. pnpm). Install deps:pnpm install - Task runner:
turbovia root scripts - Lint/format: Biome (
@biomejs/biome1.9.x) - TypeScript: 6.0.x + TypeScript 7 beta (
@typescript/native-preview) for typechecking.pnpm typecheckrunstsgo(the native preview binary) — never invoketscdirectly in scripts or docs. - Bundler:
tsdown(replaces the deprecatedtsup). App builds and library DTS emission run undertsdown. - Tests: Vitest 3.x
- Core logic: Effect TS primitives
- Postgres ORM: Drizzle
- API/ingest boundaries: Hono
- Web app: TanStack Start + React
Top-level commands (repo root)
pnpm dev— run all workspacedevtasks via Turbopnpm build— run all workspace buildspnpm check— run all workspace lint and format check scriptspnpm typecheck— run all workspace typecheckspnpm test— run all workspace testspnpm hooks— configure local git hooks for this clone
Searching the repo
grep is a shadowed shell function here, and some sources (e.g. packages/domain/spans/src/otlp/transform.ts) trip binary-file detection because of lone surrogates, which silently suppresses matches. Use command grep -a, or the dedicated search tools, before concluding a string is absent.
Git hooks (pre-commit)
- Pre-commit hook lives at
.husky/pre-commit - Pre-commit runs:
pnpm check,pnpm typecheck, andpnpm knip - Hooks are auto-configured on dependency install via root
preparescript (pnpm hooks) - Existing clones should run
pnpm hooksonce to configurecore.hooksPathand hook permissions
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.
- 9d ago First seen · 144 lines · 46 tokens per session scan B b3389b48eb64
toolchain-commands is a skill published in the GitHub repository latitude-dev/latitude-llm (4,632 stars, last pushed today), licensed MIT. It adds 46 tokens to every session and 1,551 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 2 findings (asks for root, makes network calls). 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.