SKILLEMALL.ai
GitHub ↗ RU Sign in

BF maxhub-linkedin

LinkedIn 职场数据查询助手。覆盖用户资料、公司信息、职位搜索、帖子、评论、广告等全功能，支持V1/V2双版本API。

ClawHub Hermes author: Jan丶粑粑 v3.6.1 MIT-0 10 files body ≈ 2 980 tokens Open the sourceclawhub.ai↗ analyzed 24 h ago

LinkedIn 职场数据查询助手。覆盖用户资料、公司信息、职位搜索、帖子、评论、广告等全功能，支持V1/V2双版本API。

As a process F 38/100 · Will not run — References files that are not bundled: url

IntegrationSecuritytype and topics are labelled automatically from the skill text
Runs in: OpenClaw Hermes Agent
JSON
Technical rating
B
78/100
safety, quality, tests
Safety 60%
88
Quality 40%
63
Run on models
none yet
Process rating
F
38/100
Will not run
References files that are not bundled: url
Tools and files w 18
0
Inputs and preconditions w 11
0
Consistency w 8
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. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
  3. The text references files that are not there: add them or drop the references.
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 · 12

✓ No critical or high findings

Medium and low: 12
  • low Secrets in code secret-high-entropy-token references/api-company.md:1146
    High-entropy token-like string (may be an id, hash or a credential)
    | urn | string | ✅ | >- | ACoA…L9o |
  • low Secrets in code secret-high-entropy-token references/api-company.md:1173
    High-entropy token-like string (may be an id, hash or a credential)
    | urn | string | ✅ | >- | ACoA…Wh8 |
  • low Secrets in code secret-high-entropy-token references/api-user.md:49
    High-entropy token-like string (may be an id, hash or a credential)
    | urn | string | ✅ | >- | ACoA…3hc |
  • low Secrets in code secret-high-entropy-token references/api-user.md:103
    High-entropy token-like string (may be an id, hash or a credential)
    | urn | string | ✅ | >- | ACoA…Ch4 |
  • low Secrets in code secret-high-entropy-token references/api-user.md:162
    High-entropy token-like string (may be an id, hash or a credential)
    | urn | string | ✅ | >- | ACoA…Wh8 |
  • low Secrets in code secret-high-entropy-token references/api-user.md:250
    High-entropy token-like string (may be an id, hash or a credential)
    | urn | string | ✅ | >- | ACoA…Ch4 |
  • low Secrets in code secret-high-entropy-token references/api-user.md:309
    High-entropy token-like string (may be an id, hash or a credential)
    | urn | string | ✅ | >- | ACoA…-qo |
  • low Secrets in code secret-high-entropy-token references/param-mappings.md:200
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - `urn` (string, required): >- — e.g. `ACoA…3hc`
    quoted
  • low Secrets in code secret-high-entropy-token references/param-mappings.md:208
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - `urn` (string, required): >- — e.g. `ACoA…Ch4`
    quoted
  • low Secrets in code secret-high-entropy-token references/param-mappings.md:217
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - `urn` (string, required): >- — e.g. `ACoA…Wh8`
    quoted
  • low Secrets in code secret-high-entropy-token references/param-mappings.md:237
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - `urn` (string, required): >- — e.g. `ACoA…Ch4`
    quoted
  • low Secrets in code secret-high-entropy-token references/param-mappings.md:246
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - `urn` (string, required): >- — e.g. `ACoA…-qo`
    quoted

Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 62 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
  • warning missing-ref reference to a missing file: url

Process rating: all ten parameters 38/100

Will not run. References files that are not bundled: url
  • 0Tools and files. 1 referenced file(s) missing: url
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Consistency. Frontmatter name (maxhub-linkedin) differs from the folder (linkedin-aggregate-scraper)
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Result and completion. Output format stated, no completion criterion
  • 100Steps. 45 steps
  • 100Execution cost. Instruction body is 2980 tokens

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)
  • +3Description length 62: 120–800 characters recommended
  • -229 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +4Structure: 31 headings
  • +3Step-by-step instructions: 45 items
  • +3Output format is stated explicitly
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (4 of 5)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.

External checks

ClawHub: suspicious
This LinkedIn data skill is mostly read-only, but it asks for sensitive API access and includes overbroad personal-data collection plus unrelated fallback routes that users should review before installing.
LLM: suspicious (high) · 2 Jun 2026