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AC film-production-assistant

Pre-production assistant for filmmakers. Generates script breakdowns, shot lists, call sheets, production schedules, and budget estimates from scene descriptions. Built by a working film director with 20 years on set.

ClawHub Agent Skills author: davidapx13 v1.0.1 MIT-0 23 files body ≈ 2 093 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 58/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorInfrastructuretype 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%
99
Quality 40%
87
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Risky intent intent-offensive-security references/shot-list-structure.md:46
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - **Track Left/Right** — Lateral movement on tracks

    Files scanned: 23. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "requires"

    Process rating: all ten parameters 58/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 70Failures and branches. 4 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 34 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2093 tokens
    • low 11 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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 217: enough signal without eating the budget
    • +4Structure: 27 headings
    • +3Step-by-step instructions: 34 items
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (5 of 6)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: suspicious
    The skill is a coherent film pre-production assistant, but its optional Word export uses an unsafe shell command pattern and its call-sheet workflow handles sensitive location and personnel details.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026