SKILLEMALL.ai

BC agent-manager

Multi-Agent conversation management platform with Gemini-style UI. Manage all your OpenClaw agents in one place with image upload, chat history, and message isolation.

ClawHub Hermes author: szzg007 v1.0.0 MIT-0 15 files body ≈ 181 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedurePersonal productivityAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
80/100
safety, quality, tests
Safety 60%
92
Quality 40%
62
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: agent-manager (ClawHub)

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. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
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 · 8

✓ No critical or high findings

Medium and low: 8
  • low Secrets in code secret-high-entropy-token config.json:3
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "openclawToken": "ZZit…EGM",
    quoted
  • low Secrets in code secret-high-entropy-token package-lock.json:33
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "integrity": "sha5…FFX/+gVeY…NlM++NqRc…bqg==",
    quoted
  • low Secrets in code secret-high-entropy-token package-lock.json:211
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "integrity": "sha5…FrF+LTRo…W3g==",
    quoted
  • low Secrets in code secret-high-entropy-token package-lock.json:220
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "integrity": "sha5…A6j+hAmM…GbS+kf5c…csw==",
    quoted
  • low Secrets in code secret-high-entropy-token package-lock.json:229
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "integrity": "sha5…5bm+c2gQ…aG5+esrLODihIorn+Pe6F…dXA==",
    quoted
  • low Secrets in code secret-high-entropy-token package-lock.json:408
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "integrity": "sha5…I9y+CyS8…UMQ==",
    quoted
  • low Secrets in code secret-high-entropy-token README.md:45
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "openclawToken": "ZZit…EGM",
    quoted
  • low Secrets in code secret-high-entropy-token server.js:20
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    openclawToken: 'ZZit…EGM',
    quoted

Files scanned: 15. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 167 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 18 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 181 tokens
  • 100Running it twice. No mutating operations

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
  • -2localhost URLs: will not work for another user
  • -212 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +3Description length 167: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 18 items
  • +4Has examples (3 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.

External checks

ClawHub: suspicious
This appears to be a real local OpenClaw agent manager, but it exposes powerful local controls unsafely and includes a token-like secret in the package.
LLM: suspicious (high) · VirusTotal: · 29 May 2026