SKILLEMALL.ai
RU Sign in

AB ifind

Use a local Python wrapper around the official iFinD QuantAPI HTTP endpoints on quantapi.51ifind.com. Use when the user wants iFinD market, macro, fund, code-conversion, calendar, report, or portfolio data through HTTP without downloading third-party binaries. This skill is especially appropriate when a local `ifind_api.py` wrapper or custom iFinD HTTP integration should be reused, and when refresh_token acquisition and secure local storage must be checked before any API call.

ClawHub Agent Skills author: Yann Long v1.0.0 MIT-0 8 files body ≈ 1 051 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process B 76/100 · Nearly there — weak spots: inputs and preconditions

IntegrationSoftware developmentInfrastructureData and analyticstype 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
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
94
Run on models
none yet
Process rating
B
76/100
Nearly there
Inputs and preconditions w 11
30
Tools and files w 18
60
Result and completion w 14
60
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 · 0

    ✓ No critical or high findings

    Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 76/100

    • 30Inputs and preconditions. Does not say what the process needs to start
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 31 steps
    • 100Failures and branches. 7 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1051 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress

    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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 481: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 31 items
    • +3Output format is stated explicitly
    • +4Has examples (5 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +3All 3 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 94.

    External checks

    ClawHub: suspicious
    This appears to be a legitimate iFinD API helper, but it gives the agent broad credential-backed API access and stores a long-lived token locally.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026