watch-logs SKILL.md skillA

watch-logs from understudylabs/orchestra-agent-tools is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add understudylabs/orchestra-agent-tools/watch-logs@git:20260702.51d5bca

Pins git:20260702.51d5bca in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
understudylabs/orchestra-agent-tools
Path
skills/watch-logs/SKILL.md
Versions recorded
1
Latest version
git:20260702.51d5bca, committed Jul 2, 2026
Size
5,689 bytes
Repository stars
19
License
MIT

Use when a developer wants an always-on ops watcher over logs, command output, or endpoints — "every five minutes look at my logs and tell me what's wrong", "watch this log file and flag anomalies", "review my events on a schedule without burning tokens". Deterministic hash-gated triggers fire a cheap model review only on change, and every review is captured as an eval row for a future fine-tune.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# Watch Logs

Stand up a scheduled log/event review that is cheap by construction: a
deterministic trigger script snapshots the watched sources, hashes them, and
only when the hash **changes** does an inexpensive LLM review fire. The review
itself is a small, well-bounded workload — summarize what changed, cite lines,
say "nothing wrong" honestly — sized so a tiny open model (Gemma 2B class)
could eventually serve it. Every review is recorded from day one as an
`understudy.eval_result.v1` row, so the workload accumulates training-grade
evidence without any training now.

## When to use

The developer wants recurring "look at my logs/events and tell me what's
wrong" monitoring. This skill owns the watcher loop: interview → config →
deterministic trigger → gated review → eval-row capture. For turning existing
LLM traces into evals use [`../ingest-traces/SKILL.md`](../ingest-traces/SKILL.md);
for building a frozen eval from the accumulated reviews use
[`../capture-evidence/SKILL.md`](../capture-evidence/SKILL.md); for eventually
distilling the review onto a small model use
[`../distill-classifier/SKILL.md`](../distill-classifier/SKILL.md).

## Safety Gates
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add understudylabs/orchestra-agent-tools/watch-logs@sha256:7c66207f136d96da

The line at the top of this page pins the label git:20260702.51d5bca, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_odumgorqxrbannee.svg)](https://markdownregistry.com/a/art_odumgorqxrbannee)

1 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 1 version of this file, committed on Jul 2, 2026.

versioncommittedcommitsizeaudit
git:20260702.51d5bca latest2026-07-02 51d5bca 5,689 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (5689 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

understudylabs/orchestra-agent-tools · 19 stars · license MIT · pushed 2026-11-05 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_odumgorqxrbannee
GET https://markdownregistry.com/api/v1/resolve?ref=understudylabs/orchestra-agent-tools/watch-logs
GET https://markdownregistry.com/api/v1/blob/7c66207f136d96da2c9468cc6687ab3d10e67826b9f23ffcfe0d93fd2334c6fe

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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