performance-tuning SKILL.md skillA
performance-tuning from jdanigo/hydraia is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add jdanigo/hydraia/performance-tuning@git:20260703.44486a5Pins git:20260703.44486a5 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- jdanigo/hydraia
- Path
skills/performance-tuning/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260703.44486a5, committed Jul 3, 2026
- Size
- 2,800 bytes
- Repository stars
- 8
- License
- MIT
Use when the request is a performance symptom — slow endpoint, high latency, timeouts, high CPU or memory, big bundle, slow build. Measurement-first methodology for the Hydraia perf route: baseline before analysis, numeric target in the spec, re-measure in verify. Never optimize without measuring.
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
# Performance Tuning — measure first, always The performance route through the Hydraia pipeline. The pipeline phases are unchanged; this skill defines the two contract adaptations and the hard rules. <HARD-RULES> - NO optimization without a measured baseline. If there is no number, the first deliverable is the measurement, not the fix. - The Phase 2 spec MUST contain: the baseline (metric, command, environment, runs, spread) and a NUMERIC target. A perf spec without numbers is not a spec. - One variable at a time: each plan task isolates one change so Phase 6 re-measurement can attribute the gain. - Phase 6 verify RE-MEASURES with the same commands as the baseline and compares against the target. Target missed → the run is NOT done: one more hypothesis cycle (max one), or an honest shortfall report. Never redefine the target post-hoc. - Rejected hypotheses stay in the spec — what you chose NOT to optimize and why is part of the record. </HARD-RULES> ## Route flow 1. **Symptom → metric.** Express the complaint as a measurable number (p50/p95 latency, throughput, CPU %, RSS, bundle KB, query ms). …
Read the whole file at its exact version.
How to install
mdr add jdanigo/hydraia/performance-tuning@sha256:3733f78ad5996134The line at the top of this page pins the label git:20260703.44486a5, 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.
[](https://markdownregistry.com/a/art_qv3uotxqzwecx53o)
7 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 1 version of this file, committed on Jul 3, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (2800 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
jdanigo/hydraia · 8 stars · license MIT · pushed 2026-09-24 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_qv3uotxqzwecx53o GET https://markdownregistry.com/api/v1/resolve?ref=jdanigo/hydraia/performance-tuning GET https://markdownregistry.com/api/v1/blob/3733f78ad599613484ac4cd3b0c4f0af432f1ac099ffe38fe8288aaac6f29d68
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.