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Agentic Discovery Skill

该 Skill 面向代理式开发机会的售前发现与范围界定,提供问卷、访谈指南、工作流图、数据与审批检查表、风险评估、成功标准、试点评分卡及提案/SOW 交接简报等模板,可用 Python 脚本渲染为 Markdown、PDF 和可选 PNG。它强调只收集已核实事实,未知项以 TBD 记录,并声明为本地运行、不进行外部数据回传。

completetech
completetech
热度 25.49
最近更新 2026-05-26 18:32:08
分类:效率依赖:代码执行 / 读写文件应用场景:模板 / 工作流 / 报告撰写 / 会议纪要 ...

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add agentic-discovery-skill
Metadata
name
agentic-discovery-skill
description
Create CompleteTech LLC discovery and scoping artifacts for agentic development opportunities, including intake questionnaires, workflow discovery scripts, stakeholder interview guides, current/future-state workflow maps, systems/data readiness checklists, approval gate reviews, risk/excluded-use checks, success criteria, evaluation examples, pilot readiness scorecards, and proposal/SOW handoff briefs. Use before proposal, contract, invoice, or delivery work when Codex needs to gather verified facts for bounded agentic workflow services.
version
1.0.3
metadata
{"openclaw":{"skillKey":"agentic-discovery-skill","homepage":"https://github.com/CompleteTech-LLC/agentic-discovery-skill","requires":{"bins":["python3"]},"install":[{"kind":"uv","package":"reportlab==4.5.1"},{"kind":"uv","package":"pypdfium2==5.8.0"},{"kind":"uv","package":"pillow==12.2.0"},{"kind":"uv","package":"pyyaml==6.0.3"}]}}

Agentic Discovery Skill

Purpose

Create discovery and scoping artifacts that turn an agentic development opportunity into verified facts for proposal/SOW, contract, invoice, and delivery work.

System Boundary

This skill owns pre-sale fact-finding and scoping. Hand off to agentic-proposal-skill for buyer-facing scope and SOW documents, agentic-security-review-skill for formal security or launch risk review, agentic-delivery-skill after approval, and agentic-customer-success-skill for ongoing relationship management. Do not use discovery artifacts as final proposals, contracts, invoices, launch signoffs, or public proof.

Core Workflow

  1. Identify the discovery need: qualification, intake, stakeholder interview, workflow map, readiness check, risk review, success criteria, evaluation examples, prioritization, recap, or proposal handoff.
  2. Gather verified facts only: repeated workflow, inputs, systems, tools, retrieval sources, decision points, approval gates, risks, exclusions, logging, monitoring, documentation, support, and handoff needs.
  3. Use references/use-case-decision-table.md to choose the right artifact.
  4. Use references/discovery-positioning.md for CompleteTech LLC framing and guardrails.
  5. Use references/discovery-catalog.md for near-exhaustive artifact templates.
  6. Keep discovery practical and bounded. Do not fabricate client facts, proof, savings metrics, regulated-use assurances, legal claims, or implementation feasibility.

Artifact Selection Guide

  • First-pass lead fit: use quick-qualification-checklist.
  • New opportunity intake: use client-intake-questionnaire.
  • Live discovery call: use workflow-discovery-script.
  • Multiple roles or departments: use stakeholder-interview-guide.
  • Existing process documentation: use current-state-workflow-map.
  • Proposed reviewed-agent process: use future-state-agentic-workflow-map.
  • System, document, data, or access review: use systems-and-data-access-checklist.
  • API/tool feasibility: use tool-api-readiness-checklist.
  • Approval and escalation design: use human-approval-gate-checklist.
  • Regulated, sensitive, or risky workflow: use risk-and-excluded-use-checklist.
  • Buyer asks what success looks like: use success-criteria-worksheet.
  • Need test examples: use evaluation-example-worksheet.
  • Decide whether to propose a pilot: use pilot-readiness-scorecard.
  • After discovery call: use discovery-recap-memo.
  • Handoff into proposal/SOW: use requirements-brief-for-proposal-sow-handoff.
  • Missing facts or assumptions: use assumptions-and-unknowns-log.
  • Ownership unclear: use stakeholder-responsibility-matrix.
  • Dependencies unclear: use implementation-dependency-checklist.
  • Sensitive data or retention concerns: use data-sensitivity-and-retention-worksheet.
  • Several possible workflows: use workflow-prioritization-matrix.
  • Need logging/monitoring requirements: use logging-and-monitoring-needs-worksheet.
  • Need support/handoff expectations: use support-and-handoff-discovery-worksheet.
  • Need production-readiness check: use pilot-to-production-readiness-checklist.

When several artifacts fit, choose the earliest artifact that resolves the biggest unknown. Do not draft proposal/SOW scope until the workflow, owners, approval points, success criteria, dependencies, and exclusions are clear enough to avoid vague scope.

Quality Rules

  • Frame discovery as bounded workflow scoping, not AI brainstorming.
  • Always identify human approval points for external communication, production changes, purchases, data export, and material business decisions.
  • Capture risks, excluded uses, data sensitivity, and assumptions explicitly.
  • Make outputs easy to hand to agentic-proposal-skill.
  • Use TBD or open questions for unknowns.

Resource Guide

  • references/discovery-positioning.md: load for CompleteTech LLC discovery language and boundaries.
  • references/use-case-decision-table.md: load when choosing an artifact.
  • references/discovery-lifecycle.md: load for flow from lead qualification through proposal handoff.
  • references/discovery-catalog.md: load for the near-exhaustive artifact library.
  • references/template-index.json: machine-readable template metadata used by the renderer.
  • scripts/render_discovery.py: list discovery artifacts or render a draft with placeholders.

Renderer

python3 scripts/render_discovery.py --list
python3 scripts/render_discovery.py --stage readiness --list
python3 scripts/render_discovery.py --template client-intake-questionnaire --var client_name=Acme --var workflow="support triage"

Rendered artifacts are drafts. Replace placeholders with verified client facts and refine questions for the meeting context.

Rendering to a Branded PDF

Artifacts from this skill are delivered as branded CompleteTech LLC PDF documents, not raw Markdown. The renderer emits the PDF (and prints the Markdown) in one command, using the same reportlab branding engine as the contract skill:

pip install -r requirements.txt
python3 scripts/render_discovery.py --template requirements-brief-for-proposal-sow-handoff \
  --out artifact.pdf --png artifact.png \
  --title "Requirements Brief — Proposal / SOW Handoff" --doc-type "DISCOVERY HANDOFF" \
  --subtitle "Prepared for <b>Northwind Trading Co.</b>" --meta "DOCUMENT NO.=DISC-2026-0117" --meta "DATE=2026-05-15" \
  --var client_name="Client Name" --var workflow="support triage"
  • --no-pdf emits Markdown only (the original behavior); --no-cover drops the cover page.
  • Already drafted the Markdown yourself? Render it directly: python3 scripts/render_pdf.py --markdown artifact.md --out artifact.pdf --logo assets/logo.png --title "...".
  • The PDF supports a Markdown subset: #/##/### headings, paragraphs, - bullets, tables, > callouts, **bold**, and [PAGE_BREAK]. PDF requires reportlab; the optional --png preview requires pypdfium2 and pillow. See assets/examples/ for a rendered example.

Network Boundary

This skill is local-only. It does not include outbound network helpers, callbacks, or any helper that posts discovery run metadata to an external service.