SKILLEMALL.ai

BD AIRS招投标订单采集与核查

AIRS 具身智能产业研究 Skills。面向 embodied intelligence、robotics 和机器人产业研究,将企业主体确认、天眼查招投标/中标公告采集、第三方订单核查、LLM 案例提取、标准入库表生成和案例质量复查组织为一套可复用研究流程。适用于采集公开证据、验证机器人订单、沉淀具身智能案例库和生成产业研究知识资产。 Keywords: AIRS, 具身智能, embodied intelligence, robotics, robot industry, 天眼查, tianyancha, 招投标, bidding, 中标公告, order verification, case extraction, research skills, knowledge asset.

ClawHub Agent Skills author: airs-git v1.0.2 MIT-0 32 files body ≈ 602 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, failures and branches

AnalyzerProcurementtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
95
Quality 40%
80
Run on models
none yet
Process rating
D
49/100
Unfinished process
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    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 · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Secrets in code secret-high-entropy-token package-lock.json:94
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…bKX+KS9G…yMA/NhKJ…RGz/Q==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:176
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…uyQ+a1ko…Tn4+E0Ti6C2AA==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:182
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…Wwy+ghLE…vfU/YnxW…fdg==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:210
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…DYr+NSUK…Itc/irNR…37y+AMujNyNtG+1Rggw==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:283
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…2BV+FY5ZFezP/ypmwayk68+NzzA…NFD/uUmBJuGoXw==",
      detector

    Files scanned: 26. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)

    Process rating: all ten parameters 49/100

    • 0Result and completion. Does not say what the result is
    • 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
    • 40Consistency. Frontmatter name (AIRS招投标订单采集与核查) differs from the folder (airs-embodied-intelligence-research-skills)
    • 60Tools and files. Uses tools (node) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 31 steps
    • 100Execution cost. Instruction body is 602 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
    • +2Single-language instructions
    • +3Description length 348: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 31 items
    • +4Has examples (2 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

    External checks

    ClawHub: suspicious
    This skill appears to do the research workflow it claims, but it needs Review because it uses a logged-in Tianyancha browser session and sends collected research content to a configurable LLM provider with incomplete privacy and scoping warnings.
    LLM: suspicious (high) · 28 May 2026