BD feishu-multi-agent-chat
多个 AI Agent 在飞书群聊中通过 at 互相通信，实现多 Agent 协作。覆盖建群、创建Bot、拉Bot进群、获取open_id、text格式互 at 通信、防呆约束、故障排查全流程。Use when user says 飞书多Agent通信、Bot互at、飞书Bot创建、群聊AI协作、多Bot群聊。支持 CherryClaw、WorkBuddy、OpenClaw、AutoClaw 等框架。
多个 AI Agent 在飞书群聊中通过 at 互相通信，实现多 Agent 协作。覆盖建群、创建Bot、拉Bot进群、获取openid、text格式互 at 通信、防呆约束、故障排查全流程。Use when user says 飞书多Agent通信、Bot互at、飞书Bot创建、群聊AI协作、多Bot群聊。支持…
As a process D 39/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The files contain invisible characters, encoded commands or comments hidden from readers but visible to the model. What you read differs from what the agent sees.
Remove invisible characters (they usually sneak in through copy-paste) and encoded strings: no catalog will pass them. Instructions for the model must be readable by a human too.
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 · 2
✓ No critical or high findings
Medium and low: 2
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medium Obfuscation
obf-base64-blobSKILL.md:18Long base64-looking blobRese…e1: UDxK…Inc+578S…DIk+5rPK…2dA+h/HYhX…2CG+1xGvSSGYQ
-
medium Obfuscation
obf-base64-blobSKILL.md:21Long base64-looking blobRese…e2: UDxK…Inc+578S…DIk+5rPK…2dA+h/HYhX…2CG+1xGvSSGYQ
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "keywords" - note
frontmatter-keyunknown frontmatter key "tested" - note
frontmatter-keyunknown frontmatter key "AIGC"
Process rating: all ten parameters 39/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 7 mutating operations with no state check
- 40Consistency. Frontmatter name (feishu-multi-agent-chat) differs from the folder (feishu-agent-communication)
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 100Steps. 23 steps
- 100Execution cost. Instruction body is 1428 tokens
- low 12 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 202: enough signal without eating the budget
- +4Structure: 22 headings
- +3Step-by-step instructions: 23 items
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.