Documentation Index
Fetch the complete documentation index at: https://docs.selftune.dev/llms.txt
Use this file to discover all available pages before exploring further.
Overview
selftune grades skill execution across three tiers, from basic trigger detection to output quality assessment.The 3 tiers
Tier 1: Trigger
Did the skill fire at all? This is the most fundamental check. When a user query should have activated a skill, did it? Tier 1 catches false negatives — queries that match a skill’s intent but the skill stayed silent.Tier 2: Process
Did the agent follow the right steps? Once a skill fires, did the agent execute the workflow correctly? This checks whether the agent followed the SKILL.md instructions, used the right tools, and completed the expected steps.Tier 3: Quality
Was the output actually good? The final tier evaluates whether the end result met the user’s needs. A skill can trigger correctly and follow the right process but still produce a poor result.Scoring
Each tier produces a score from 0.0 to 1.0. The overall grade is one of:| Grade | Meaning |
|---|---|
| pass | Skill triggered correctly and executed well |
| partial | Skill triggered but execution had issues |
| fail | Skill didn’t trigger or execution failed |
Deterministic pre-gates
Before making any LLM calls, selftune runs deterministic pre-gate checks that resolve in under 20ms. These handle obvious cases without spending tokens:- Exact keyword matches
- Known negative patterns
- Previously graded identical queries
Running grades
Seeselftune grade for the full command reference.
Grade a specific skill: