search-index-tuning
Skill1 starsChanged 9 months agoMITView on GitHub
Build and tune search/index pipelines with deterministic relevance behavior and measured query/indexing performance.
In this repository15 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .claude/CLAUDE.mdCLAUDE.md
- CLAUDE.mdCLAUDE.md
- .github/copilot-instructions.mdCopilot instructions
- chaos-fuzz-runnerSkill
- data-migration-safetySkill
- external-integration-reliabilitySkill
- failure-forensicsSkill
- harmonization-operatorSkill
- hud-control-opsSkill
- mcp-policy-opsSkill
- smoke-gate-runnerSkill
- sync-conflict-playbookSkill
- track-contract-authorSkill
- transaction-concurrency-guardSkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 8
Use this skill for full-text or large-query retrieval behavior.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Search Index Tuning
Use this skill for full-text or large-query retrieval behavior.
Workflow
- Define retrieval contract:
- searchable fields
- ranking priorities
- stemming/tokenization rules
- Choose index strategy:
- FTS engine
- composite/covering indices
- update trigger path
- Measure and tune:
- query plan inspection
- p95 latency targets
- indexing throughput and staleness window
- Validate relevance regressions with fixture-based ranking tests.
Failure Modes To Handle
- Fast but irrelevant results.
- Relevance drift after schema/content changes.
- Index update lag causing stale search output.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.