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AD agentic-proposal-skill

Create CompleteTech LLC agentic development proposals, statements of work, discovery recaps, pilot recommendations, evaluation plans, risk/control plans, implementation roadmaps, acceptance criteria, change orders, retainer proposals, and procurement-ready scope summaries. Use when Codex needs to bridge outreach emails and signed contracts/invoices by drafting buyer-facing proposal or SOW-style documents for bounded agentic workflow services.

ClawHub Agent Skills author: CompleteTech v1.0.2 MIT-0 20 files body ≈ 1 625 tokens Open the sourceclawhub.ai↗ analyzed 25 h ago

Create CompleteTech LLC agentic development proposals, statements of work, discovery recaps, pilot recommendations, evaluation plans, risk/control plans…

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

GeneratorAI and agentstype 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
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
Run on models
none yet
Process rating
D
49/100
Unfinished process
Inputs and preconditions w 11
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 · 0

    ✓ No critical or high findings

    Files scanned: 20. 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 49/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 3 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 100Steps. 46 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1625 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)
    • +3Output format is not stated: the model decides each time
    • -5TODO / placeholder text left in the skill
    • -31 of 3 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 446: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 46 items
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (4 of 4)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

    External checks

    ClawHub: clean
    This is a local proposal and PDF drafting helper; the main caution is dependency hygiene, not hidden or harmful behavior.
    LLM: benign (high) · VirusTotal: · 28 May 2026