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REST API instructions for FlowFi—authorization, smart accounts, workflows (AI generate, edit, deploy, undeploy, delete, pause, resume, stop), execution (list, start, cancel, events), WebSocket (workflow-status namespace, subscribe execution/workflow/simulation), price (token/USD), templates (list, get, clone), DTO/request/response shapes (pagination, workflow, template, execution), and workflow knowledge base. Use when integrating with the backend API or when the user asks about workflow, execution, real-time, price, templates, DTOs, or auth endpoints.

ClawHub Agent Skills author: devarogundade v1.0.3 14 files body ≈ 340 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process D 42/100 · Unfinished process — weak spots: steps, result and completion, inputs and preconditions

ProcedureInfrastructuretype 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
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
D
42/100
Unfinished process
Steps w 15
0
Result and completion w 14
0
Inputs and preconditions w 11
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 · 0

    ✓ No critical or high findings

    Files scanned: 14. 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 42/100

    • 0Steps. Prose only: no discrete steps
    • 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
    • 30Running it twice. 4 mutating operations with no state check
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 340 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)
    • +4Structure: 1 headings, hard to scan
    • +3No numbered steps or checklist
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 558: enough signal without eating the budget
    • +4Reference files are cited in the instructions (11 of 11)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

    External checks

    ClawHub: suspicious
    FlowFi is a coherent API documentation skill, but it asks agents to handle bearer tokens and perform high-impact workflow mutations without enough user-confirmation or token-safety guidance.
    LLM: suspicious (high) · VirusTotal: benign · 28 May 2026