microsoft/sre-agent is the community repository for Azure SRE Agent, an AI assistant for diagnosing and resolving production problems and reducing routine operations work. It is for teams working on service reliability and includes documentation, discussions, videos, and hands-on labs for using the product. The catalogue skills relate to the agent's official plugins and resources.
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 microsoft/sre-agent --skill redaction-guardgit clone --depth 1 https://github.com/microsoft/sre-agentWrote 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/microsoft/sre-agent/redaction-guard)<a href="https://agentmods.dev/skills/microsoft/sre-agent/redaction-guard"><img src="https://agentmods.dev/badge/skills/microsoft/sre-agent/redaction-guard/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/microsoft/sre-agent/redaction-guard"><img src="https://agentmods.dev/badge/skills/microsoft/sre-agent/redaction-guard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 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 41 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 16 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 29 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 41 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 | $0.00105 | $0.00858 |
| Opus 5.5 | $0.00042 | $0.00343 |
| Sonnet 5.5 | $0.00021 | $0.00172 |
| Haiku 4.5 | $0.00011 | $0.00086 |
Grade A, and why
redaction-guard 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Zava Learning — Redaction Guard
A cross-cutting safety layer: nothing sensitive ever reaches an operator-visible surface. The triggering alert is symptom-only and the investigation touches Key Vault secrets, connection strings, access tokens and learner PII — none of which may be exposed in chat, notes, PRs, or reports.
Load the standard, then scrub
Retrieve the canonical policy and scrubber with SearchMemory("zava-redaction"). It defines what
counts as sensitive, the credential files you must never print, and a deterministic redact()
function. Apply redact() (via ExecutePythonCode) to every string you are about to emit —
chat summary, note body, PR/commit text, and the assembled HTML/markdown/deck — before it leaves the
agent. The scrubber is idempotent, so running it more than once is safe.
What to redact (summary — see zava-redaction for the full list)
- Secrets & credentials: passwords,
PGPASSWORD, connection strings, Key Vault secret values, client secrets, API / access / account keys, SAS tokens. - Tokens: GitHub PATs (
gho_/ghp_/github_pat_…), JWTs / AAD access tokens (eyJ…), bearer /Authorizationvalues. - Private keys: any
-----BEGIN … PRIVATE KEY-----block, SSH/cert keys. - Credentials inside URIs: the password in
scheme://user:password@host. - PII: email addresses and learner personal data from the database.
Keep resource names, resource groups, regions, app names, alert names, and PR/CR numbers — they are not sensitive and are needed for the narrative.
Hard rules
- Never read or print credential files. Reference them by name only — never
cat/Get-Content/echo/typethe contents of.git/git-credentials,.env,*.pem,id_rsa*,*.pfx,kubeconfig,~/.azure/*, or*.tfstateinto the thread or a report. - When a command can echo a secret (e.g.
az keyvault secret show), do not paste its output — confirm the fact ("secret present / rotated") without revealing the value. - When in doubt, redact. Replace with
[REDACTED:<CLASS>]; for URI credentials keep the scheme and username and mask only the password.
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 · 58 lines · 105 tokens per session scan A aee80cd3f74b
redaction-guard is a skill published in the GitHub repository microsoft/sre-agent (179 stars, last pushed 3d ago), licensed MIT. It adds 105 tokens to every session and 858 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 2026-08-30.
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