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BC avengers-assemble

Avengers-themed multi-agent coordination system. Nick Fury orchestrates 6 specialized heroes (Captain America, Iron Man, Hulk, Black Widow, Hawkeye, Thor) through sessions_spawn delegation. Round-robin dispatch, reply-first protocol, sessionKey reuse. Perfect for complex tasks requiring diverse expertise and coordinated team execution.

ClawHub Agent Skills author: ChenXinBest v1.0.0 MIT-0 4 files body ≈ 5 724 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
59
Run on models
none yet
Process rating
C
54/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • 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: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 5724 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "keywords"

Process rating: all ten parameters 54/100

  • 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. 31 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 70Execution cost. Instruction body is 5724 tokens
  • 100Tools and files. No external tools needed
  • 100Steps. 77 steps
  • 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 16 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
  • -238 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 337: enough signal without eating the budget
  • +4Structure: 58 headings
  • +3Step-by-step instructions: 77 items
  • +4Has examples (4 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.

External checks

ClawHub: clean
This skill is a disclosed multi-agent coordinator; its main risks are expected delegation and reused session memory, not hidden or malicious behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026