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/fix-datadog-issues/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/fix-datadog-issues)<a href="https://agentmods.dev/skills/latitude-dev/latitude-llm/fix-datadog-issues"><img src="https://agentmods.dev/badge/skills/latitude-dev/latitude-llm/fix-datadog-issues.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 5.1 | $0.00076 | $0.05445 |
| Opus 5 | $0.00038 | $0.02722 |
| Sonnet 5 | $0.00015 | $0.01089 |
| Haiku 4.5 | $0.00008 | $0.00545 |
Grade A, and why
fix-datadog-issues 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 7d 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 — 355 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fix Datadog Error Tracking issues
This skill takes a brand-new agent from "look at Datadog" all the way to a reviewable PR. You will run it repeatedly across separate, context-free sessions, so it is written to be restartable: a fixed error simply stops receiving occurrences, and (when the tooling allows) you leave a comment on the issue so the next agent does not redo your analysis.
The Datadog MCP server is plugin:datadog:mcp. Its tools are deferred — their schemas load on
demand. Load them with ToolSearch (e.g. select:mcp__plugin_datadog_mcp__aggregate_spans) before
calling, and run the server's skill-discovery first (see §1).
The pipeline (overview)
0. Setup & disambiguate → 1. Navigate Datadog → 2. Pick an issue → 3. Root-cause in code
→ 4. ⛔ CONFIRM PLAN WITH USER → 5. Reproduce with tests + fix → 6. Comment on the issue → 7. PR to development
Hard gate at step 4: you investigate freely, but you do not write a fix, create a branch, or open a PR until the user has seen your plan and approved it (see §4). The only exception is explicit pre-authorization (e.g. "just fix it and PR").
Do not try to fix every issue. Scope a PR by size/risk (see §2.4): one big/critical bug = its own PR; a few small, independent, related bugs may share one PR (cap ~4).
0. Setup and critical disambiguations
Read these first — each one was a real wall that cost time.
-
"Incidents" almost always means Error Tracking issues, not Incident Management. Datadog Incident Management (
search_datadog_incidents) is typically empty (0) here, and incidents have no "occurrences". When the user says incidents / issues / errors / "most occurrences" / "newest", they mean Error Tracking (errors grouped into issues, with occurrence counts and trends). -
Only v2 services are fixable from this repo. This repo (
latitude-v2, trunkdevelopment) owns:api,ingest,web,workers,workflows. Thelatitude-llm-*services (latitude-llm-web,latitude-llm-workers,latitude-llm-gateway, …) are the legacy v1 codebase (branchlatitude-v1) — out of scope unless the user says otherwise. Derive the live v2 list fromls apps/so it never goes stale.
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.
- 7d ago First seen · 355 lines · 76 tokens per session scan A c11949b8dd2c
fix-datadog-issues is a skill published in the GitHub repository latitude-dev/latitude-llm (4,629 stars, last pushed yesterday), licensed MIT. It adds 76 tokens to every session and 5,445 once invoked, about $0.0004 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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