BB text-optimize
Optimizes text, docs and LLM prompts (CLAUDE.md, rules, agent/skill files) for token efficiency in place, snapshot-backed, without losing facts. Use when asked to optimize, compress or cut tokens of named files. Triggers - optimize, reduce tokens, compress, deep compress, сожми, оптимизируй.
Optimizes text, docs and LLM prompts (CLAUDE.md, rules, agent/skill files) for token efficiency in place, snapshot-backed, without losing facts. Use when…
As a process B 68/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, running it twice
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 5674 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 68/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 14 mutating operations with no state check
- 55Failures and branches. 1 branches
- 70Execution cost. Instruction body is 5674 tokens
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 52 steps
- 100Result and completion. Output format and completion criterion are stated
- 100Consistency. Name and required fields are in place
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 17 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (4 tags): a typed call is more reliable
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- -31 of 2 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 292: enough signal without eating the budget
- +4Structure: 31 headings
- +3Step-by-step instructions: 52 items
- +3Output format is stated explicitly
- +4Has examples (9 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.