performance-profiling skillA
performance-profiling is agent-read markdown (skill) from nahid-sparktales/agent-dispatcher: Find where the time actually goes before changing anything — define the metric and workload, build a repeatable baseline with its spread, profile on the right axis, confirm the suspected hotspot by removing its work, then re-measure under identical conditions. Use when something is slow, when an optimization is about to be written from a hunch, or when a speedup is being claimed without comparable numbers. Not for reading code to guess what is expensive, not for micro-tuning with no measured use.
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# Performance profiling The function that looks expensive and the function that is expensive are two different populations with a modest overlap. Every optimization written before a profile is a guess with a diff attached. ## When this fires - Something is measurably slow, or a latency, memory or throughput target is being missed. - An optimization is about to be written on the strength of how the code reads. - A speedup is being reported without a baseline, a spread, or comparable conditions. It does not fire for correctness work, and it does not fire for a change whose only justification is that a faster construct exists — a faster loop inside 2% of the runtime is not an improvement, it is churn. ## Procedure 1. **Define the metric and the workload.** "Slow" is not a metric. Pick one: p95 latency of this request under this load, peak resident memory, time to first byte, wall-clock of this job, rows per second. Say which environment, which data, and what would count as good enough. 2. **Reproduce the slowness in a harness you can run repeatedly**, with representative data. …
Read the whole file at its exact version.
How to install
mdr add nahid-sparktales/agent-dispatcher/performance-profiling@git:20260919.a0d4f55mdr add nahid-sparktales/agent-dispatcher/performance-profiling@sha256:f8024c9061325c6ePin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_izyltbco2lxqo5ri)
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Versions
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 (7176 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
nahid-sparktales/agent-dispatcher · 49 stars · license MIT · pushed 2026-09-23 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_izyltbco2lxqo5ri GET https://markdownregistry.com/api/v1/resolve?ref=nahid-sparktales/agent-dispatcher/performance-profiling GET https://markdownregistry.com/api/v1/blob/f8024c9061325c6eff10d71a6fccc00db17d1cec2e4f14f5f168ab483ebbea21
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