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/env-configuration/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/env-configuration)<a href="https://agentmods.dev/skills/latitude-dev/latitude-llm/env-configuration"><img src="https://agentmods.dev/badge/skills/latitude-dev/latitude-llm/env-configuration.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 45 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.
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 | $0.00028 | $0.00899 |
| Opus 5 | $0.00014 | $0.00449 |
| Sonnet 5 | $0.00006 | $0.00180 |
| Haiku 4.5 | $0.00003 | $0.00090 |
Grade A, and why
env-configuration 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 8d 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Environment configuration
When to use: Adding or reading env vars, updating .env.example, or validating config at startup with parseEnv / parseEnvOptional.
LAT_ prefix convention
All application environment variables must be prefixed with LAT_ so they do not collide with third-party services, Docker, or common names.
Use LAT_ for:
- Database URLs and pool settings (
LAT_DATABASE_URL,LAT_PG_POOL_MAX, …) - Service endpoints the app reads (
LAT_CLICKHOUSE_URL,LAT_REDIS_HOST, …) - App ports (
LAT_API_PORT,LAT_WEB_PORT,LAT_INGEST_PORT) - Auth, email, OAuth, billing, CORS (
LAT_BETTER_AUTH_SECRET,LAT_MAILPIT_HOST, …) - Any new variable consumed by Latitude application code
Do not use LAT_ for:
NODE_ENV- Docker-only init variables (
POSTGRES_USER,CLICKHOUSE_USER, …) - Config read only by container images (Weaviate, Redis in compose, etc.)
- Browser-exposed Vite vars: use
VITE_LAT_*(Vite requires theVITE_prefix)
Reference: .env.example lists Docker “Services” vs “Latitude Application” (LAT_*) variables.
.env.example maintenance
Every new variable must appear in .env.example:
- Required: uncommented with a sensible local default (e.g.
LAT_API_PORT=3001) - Optional: commented with a placeholder (e.g.
# LAT_STRIPE_SECRET_KEY=sk_test_xxx)
Keep the self-host surfaces in sync
Self-hosters configure Latitude through these env vars, so adding, renaming, or removing one means updating more than .env.example. Whenever you touch a LAT_* var, also reflect it in:
- The configuration reference
docs/deployment/configuration.mdx— so operators know what the var does — unless it is specific to Latitude's own cloud deployment, which stays out of the self-host docs: payments/Stripe, marketing/lifecycle email (Loops), support chat (Intercom), and internal analytics/observability vendors (PostHog, Datadog/OTEL export, GTM, Framer, ipinfo). General app/infra/auth/AI/email-transport vars all belong in the reference. - The Helm chart
charts/latitude/— decide where the var belongs:- non-secret →
templates/configmap.yaml(and avalues.yamlknob if it's a first-class setting); - secret →
templates/secret.yamland the chart README'sexistingSecretkey list; - optional/rare → no template change needed; the documented
config.extraEnv/secrets.extrapass-through already covers it.
- non-secret →
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.
- 8d ago First seen · 67 lines · 28 tokens per session scan A 381699f6e86b
env-configuration is a skill published in the GitHub repository latitude-dev/latitude-llm (4,631 stars, last pushed today), licensed MIT. It adds 28 tokens to every session and 899 once invoked, about $0.0001 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.
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.