AD token-economy
Full token economy suite for OpenClaw agents. Audits context window usage (skills, history, tool outputs), then applies 5 creative strategies to reduce bloat without losing memory quality. Use when asked to "analyze tokens", "reduce context", "find bloat", "optimize memory", or "distill history".
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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: 15. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "tools_required" - note
frontmatter-keyunknown frontmatter key "scripts"
Process rating: all ten parameters 49/100
- 0Result and completion. Does not say what the result is
- 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. 3 mutating operations with no state check
- 40Consistency. Frontmatter name (token-economy) differs from the folder (token-optimizer-skills)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 27 steps
- 100Failures and branches. 1 branches, has a failure section
- 100Execution cost. Instruction body is 3318 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 5 example trigger phrases
- +3Description length 297: enough signal without eating the budget
- +4Structure: 17 headings
- +3Step-by-step instructions: 27 items
- +4Has examples (11 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.