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AC didit-sessions

Integrate Didit Session & Workflow APIs — the central hub for managing verification sessions. Use when the user wants to create a verification session, set up a KYC workflow, create a session with a workflow_id, retrieve session results, get session decisions, list sessions, delete sessions, update session status, approve or decline sessions, request resubmission, generate PDF reports, share sessions between partners, import shared sessions, add or remove users from blocklist, manage blocked faces/documents/phones/emails, handle webhooks, or implement any end-to-end verification flow using Didit. Covers 11 API endpoints: create, retrieve, list, delete, update-status, generate-pdf, share, import-shared, blocklist-add, blocklist-remove, blocklist-list.

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 3 703 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Integrate Didit Session & Workflow APIs — the central hub for managing verification sessions.

As a process C 54/100 · Has gaps — weak spots: steps, inputs and preconditions, running it twice

ProcedurePDFData and analyticsSoftware developmenttype 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
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
C
54/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
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: 1. 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 54/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 14 mutating operations with no state check
    • 43Steps. 2 steps, 1 vague phrases
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash) 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
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3703 tokens
    • low 17 top-level sections: this looks like several domains in one skill

    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)
    • +3No numbered steps or checklist
    • +1No license
    • +2Single-language instructions
    • +3Description length 760: enough signal without eating the budget
    • +4Structure: 27 headings
    • +3Output format is stated explicitly
    • +4Has examples (29 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.