danyuchn

    danyuchn/asd-ste100-skill

    #87 this week

    ASD-STE100 Simplified Technical English rules, repurposed as a Claude Code skill for rewriting ambiguous agent-facing English.

    backend
    Python
    MIT
    4.7K stars
    272 forks
    4.7K GitHub watchers
    Updated Oct 13, 2026
    View on GitHub

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    Where it stands

    Rank, growth pace and release cadence relative to everything GStars tracks.

    Ranks #87 of 2,503 repositories GStars tracks this week (top 3%).

    This week's +1,006 stars is ahead of its 30-day pace of about +629 per week.

    The project lists 9 contributors on GitHub.

    Peaked at #87 in the weekly ranking the week of Oct 11, its best in the past year.

    Use Cases & Benefits

    • Rewrites ambiguous English text into ASD-STE100 Simplified Technical English to ensure clarity for AI agents parsing agent-facing messages.
    • Enforces strict linguistic rules to eliminate ambiguity, enabling reliable machine-to-machine communication without human intervention.
    • Use for clarifying error messages and tool descriptions to prevent misinterpretation by downstream AI agents.
    • Use for simplifying inter-agent instructions and system prompts to ensure precise understanding in automated workflows.
    • Use for linting and rewriting technical prose in AI-generated documentation to maintain consistent, unambiguous language.

    Should you depend on it?

    License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.

    License

    MIT

    Permissive: commercial use, modification and redistribution are allowed with attribution.

    Community files

    • README: present

    Watch-outs

    • No GitHub releases; pin a commit or tag instead of a release.

    General guidance from repository metadata, not legal advice. How we score

    From the README

    A Claude Code skill that rewrites dense, ambiguous English into ASD-STE100 Simplified Technical English (STE) — the controlled-language standard the aerospace and defense industry built so aircraft maintenance instructions cannot be misread.

    This skill repurposes that same discipline for a different reader: an AI agent parsing another agent's output, a tool description, an error message, or an inter-agent instruction, with no human in the loop to resolve ambiguity.

    STE exists because a misread instruction on an aircraft can kill people, and the intended readers were often not native English speakers with no author to call for clarification. The standard's fix: one meaning per word, active voice, simple tenses, one instruction per sentence, short sentences, no dropped words.

    An LLM agent parsing another agent's output is in a strikingly similar position — no back-channel, no way to ask "did you mean X or Y?" The same rules that keep a mechanic from misreading a torque spec keep a downstream agent from misreading a tool description or an inter-agent message.

    More examples, including illustrations of the official STE rules themselves, in examples/before-after.md.

    Excerpt from the danyuchn/asd-ste100-skill README on GitHub (MIT license). © its authors.Read the full README on GitHub

    Daily snapshots

    Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots

    Oct 11: +104Oct 12: +161Oct 13: +120

    +385 stars over 3 days across 4 snapshot days; best day +161 on Oct 12.

    Forks

    272+24

    Open issues

    6+1

    Compared with peers in Backend

    Fastest-growing repositories GStars tracks in this cohort for the week of Oct 11, by 7-day star growth

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