build/skills/prompt-prose-writer/SKILL.md
Apply prompt-design rules when authoring or planning prompt-prose deliverables. Detects whether a deliverable IS prompt prose, and only then Reads the rules and applies R1-R7 before drafting. Preloaded by agent files that may author prompt prose.
npx skillsauth add dfrysinger/qrspi-plus build/skills/prompt-prose-writerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Prompt prose is text authored to be loaded into an LLM's context as instructions, system prompts, agent definitions, skill definitions, reviewer rubrics, MCP tool descriptions, RAG instructions, or any equivalent LLM-consumable directive content.
Detection rule (universal). Use content semantics, not just file path or extension, as the determining signal. Ask: is the text intended to be loaded into an LLM's context at runtime as instructions? If yes, it is prompt prose, regardless of where it lives in the repo.
Path and extension as secondary signals (fast-path shortcut for qrspi-plus-internal authoring). When ALL target files match one of these globs, classify as prompt prose without further inspection:
skills/**/SKILL.mdskills/**/*.md (snippet files under a skill directory)agents/*.mdAGENTS.mdCLAUDE.mdFiles outside these globs require the content-semantic test above. Other projects may carry prompts in prompts/, src/llm-instructions/, or custom layouts — the content-semantic test is universal; the glob list is qrspi-plus-internal convenience only.
Examples of prompt prose:
agents/*.md file defining a subagent (role, task, constraints, tools)..md file under a project's prompts/ directory whose frontmatter description: indicates LLM consumption.<HARD-GATE> blocks)..txt or .json file whose content is plainly an LLM instruction payload.Examples of NOT prompt prose:
<!-- prose-design: ... --> marker indicates a verbatim prompt-prose block within).Rules file. When prompt-prose authoring or review applies, the rules live at skills/_shared/prompt-design-rules.md (resolved from the installed plugin path per host convention).
Writer-side application. When authoring or planning a deliverable, apply the detection above to the planned target content (or sub-block, for blocks within larger documents like design.md). If the target IS prompt prose, Read skills/_shared/prompt-design-rules.md (resolved from the installed plugin path per host convention) and apply R1-R7 + cross-cutting principles BEFORE drafting, not as post-write polish. The rules shape what to write; patching after the fact is a known anti-pattern. If the Read fails, do NOT proceed with authoring. Surface the error and stop.
If the target is NOT prompt prose (ordinary documentation, configuration, code, non-prompt prose), do NOT Read the rules file. Reading-without-applying is the verbosity-bias anti-pattern the rules themselves warn against — loading them into context for a deliverable they don't apply to wastes context and risks misapplication.
<!-- INCLUDE-END: prompt-prose-writer-addition --> <!-- Guard: if you do not see content between any INCLUDE-BEGIN/INCLUDE-END pair above, do NOT apply this skill. Surface a load error naming the missing block and stop — partial context is worse than no skill. -->development
Cross-cutting QRSPI reviewer protocol — finding schema, change-type classifier, untrusted-data handling, and dispatch contract. Per-channel emission contracts live in sibling files first-party-emission.md and third-party-emission.md.
development
Use when starting any conversation — establishes the QRSPI pipeline for agentic software development, requiring structured progression through Goals, Questions, Research, Design, Phasing, Structure, Plan, Parallelize, Implement, Integrate, Test, with Replan firing between phases
development
Use when questions.md is approved and the QRSPI pipeline needs objective codebase and web research — dispatches parallel specialist subagents per question, collates per-question findings into research/summary.md
development
Use when goals.md is approved and the QRSPI pipeline needs research questions generated — produces tagged questions that guide the Research step without leaking goals