OpenSRE is an open-source framework for building AI agents that investigate and resolve production incidents using operational data and tools. It is for site reliability engineers who want customizable incident-response workflows, training, and evaluation on their own infrastructure.
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 skills add Tracer-Cloud/opensre --skill analyzing-local-repositoriesgit clone --depth 1 https://github.com/Tracer-Cloud/opensreWrote 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/tracer-cloud/opensre/analyzing-local-repositories)<a href="https://agentmods.dev/skills/tracer-cloud/opensre/analyzing-local-repositories"><img src="https://agentmods.dev/badge/skills/tracer-cloud/opensre/analyzing-local-repositories/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/tracer-cloud/opensre/analyzing-local-repositories"><img src="https://agentmods.dev/badge/skills/tracer-cloud/opensre/analyzing-local-repositories.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00112 | $0.02204 |
| Opus 5.5 | $0.00045 | $0.00882 |
| Sonnet 5.5 | $0.00022 | $0.00441 |
| Haiku 4.5 | $0.00011 | $0.00220 |
Grade A, and why
analyzing-local-repositories 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 11d 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 — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Local repository insights
Show the user what their own repositories say about how they work, read from git on this machine with no GitHub token and no network, then offer the next step. This often runs in a user's first session, after GitHub could not be used, so it must end with something about their own work, never with only a blocker.
Plan
After reading this skill, use update_plan to create the live Local Insights
plan from the four numbered workflow headings below. Mark a step in_progress
or completed in the same response as that step's tool call. Mark step 1 with
verifies: true and step 2 with deliverable: true in every update_plan
call: step 2's work is the reply itself.
- Step 1. Read the local repositories with analyze_local_repositories.
- Step 2. Show the local insights report as a text-only reply.
- Step 3. Use ask_user_choice to ask what to watch and what comes next.
- Step 4. Save what to watch with memory_remember and start the chosen next step.
Workflow
1. Read the local repositories
Call analyze_local_repositories with:
reason:github_not_connectedwhen the user chose their local repositories at the GitHub setup menu, or GitHub has no token;github_failedwhenanalyze_github_ci_reliabilitycould not read GitHub; pass itserror_kindasgithub_errorwhen it named one;no_github_actionswhen the user picked a repository marked(local insights);requestedotherwise.
repository: the repository the user picked earlier in this session, asowner/repoor its local path, if any.paths: thepathof each repository in this session'sscan_local_git_workspaceresult, the picked repository's own path first, then the most active ones, when a scan ran. Omit it otherwise; the tool scans.
Complete when analyze_local_repositories has returned in this turn. If it
returned cancelled, stop. If it returned success: false with an error,
say in one line that the local repositories could not be read, and stop. If
this build has no analyze_local_repositories tool, say in one line that
opensre update adds this report, and stop.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 167 lines · 112 tokens per session scan A fbfad3cdc1b0
analyzing-local-repositories is a skill published in the GitHub repository Tracer-Cloud/opensre (11,969 stars, last pushed today), licensed Apache-2.0. It adds 112 tokens to every session and 2,204 once invoked, about $0.0004 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 2026-10-05.
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