AB openclaw-feishu-reasoning-ux
Improve OpenClaw's Feishu reply experience by customizing streaming cards, raw reasoning visibility, card 2.0 layouts, collapsible panels, titles, colors, and fallback send paths. Use this whenever a user wants a better Feishu reply UX for OpenClaw, especially when raw reasoning disappeared, only Thinking shows, titles/styles regressed, cards feel too black-box, or the user wants Feishu replies to become more observable, layered, and customizable.
As a process B 69/100 · Nearly there — weak spots: result and completion, 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: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 6967 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 69/100
- 0Result and completion. Does not say what the result is
- 30Running it twice. 26 mutating operations with no state check
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 6967 tokens
- 85Steps. 365 steps, 2 vague phrases
- 100When it triggers. States when to use and when not to
- 100Failures and branches. 26 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 23 top-level sections: this looks like several domains in one skill
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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 451: enough signal without eating the budget
- +4Structure: 48 headings
- +3Step-by-step instructions: 365 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (1 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.