prompt-architecture
Skill1 starsChanged 5 months agoMITView on GitHub
Provide a structural recipe for authoring multi-section prompts (Persona, Context, Constraints, Toolset, Output Schema, Examples, Anti-patterns) that compose cleanly across our prompts/, agents/, and skills/core/ layers. The recipe is load-bearing: the Anti-patterns section is the single biggest predictor of prompt quality because it blocks the most common failure modes before the model generates. Use when authoring a new prompt, refactoring a sprawling prompt that drifts in quality, or migrating a hard-coded prompt into the prompts/ skill layer. Choose this skill…
1 other project uses a version of this.
Adopted by
Most recently taken up by
- nikzlabs/shipittheir own version, first seen Oct 28, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- nikzlabs/shipit★ 9same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository117 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- advanced-orchestrationSkill
- architect-agentSkill
- implementer-agentSkill
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- adaptive-prompt-selectionSkill
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- grill-user-before-buildingSkill
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- incremental-reviewSkill
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- lessons-learned-dbSkill
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- plan-driven-executionSkill
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- prd-from-contextSkill
- project-constitutionSkill
- prototype-before-commitmentSkill
- quality-engineSkill
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- The first 60 shown.
The file
We split this skill into the rules it gives an agent
8 rules. About 0 are common, 6 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈6
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 32
Write the Persona section in one or two sentences: who is the model in this prompt, and what is its scope.
- Distinctive: line 33
Write the Context section: the inputs the model has, the inputs it does not have, and the assumptions it should make.
- Distinctive: line 34
Write the Constraints section: hard limits (token budget, time, scope), soft preferences (style, verbosity), and non-goals (what the prompt …
- Very specific: line 35
Write the Toolset section: which tools the model may call, in what order, and with what guard rails (e.g., npm run validate:all before …
- Distinctive: line 36
Write the Output Schema section: the exact shape the caller expects.
- Distinctive: line 37
Write the Examples section: at least one positive example (desired output) and one negative example (a common wrong output to avoid).
- Distinctive: line 38
Write the Anti-patterns section: at least 3 concrete failure modes the prompt is known to fall into, with the corrective action for each.
- Very specific: line 39
Verify the prompt under the verification-before-done 5-axis framework: DOM (output structure), Console (errors/warnings), Network (tool …
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Skill: Prompt Architecture
Purpose
Provide a structural recipe for authoring multi-section prompts (Persona, Context, Constraints, Toolset, Output Schema, Examples, Anti-patterns) that compose cleanly across our prompts/, agents/, and skills/core/ layers. The recipe is load-bearing: the Anti-patterns section is the single biggest predictor of prompt quality because it blocks the most common failure modes before the model generates.
When to use
Use when authoring a new prompt, refactoring a sprawling prompt that drifts in quality, or migrating a hard-coded prompt into the prompts/ skill layer. Choose this skill when you need a documented structure with concrete section contracts — not a freeform "be a good prompt engineer" hand-wave.
Inputs
- The prompt's purpose (one sentence, verb-first).
- The model profile (
lean= short,standard= balanced,heavy= structured). - The agent or skill that will invoke the prompt.
- The output schema the caller expects (markdown, JSON, YAML, plain text).
- Known failure modes to block in the Anti-patterns section.
Workflow
- Write the Persona section in one or two sentences: who is the model in this prompt, and what is its scope. Avoid role-playing a real person.
- Write the Context section: the inputs the model has, the inputs it does not have, and the assumptions it should make. List them — do not bury them in prose.
- Write the Constraints section: hard limits (token budget, time, scope), soft preferences (style, verbosity), and non-goals (what the prompt explicitly does not try to do).
- Write the Toolset section: which tools the model may call, in what order, and with what guard rails (e.g.,
npm run validate:allbefore declaring done). - Write the Output Schema section: the exact shape the caller expects. Use a fenced block with a worked example.
- Write the Examples section: at least one positive example (desired output) and one negative example (a common wrong output to avoid).
- Write the Anti-patterns section: at least 3 concrete failure modes the prompt is known to fall into, with the corrective action for each. This section is load-bearing.
- Verify the prompt under the
verification-before-done5-axis framework: DOM (output structure), Console (errors/warnings), Network (tool calls), Performance (latency), Visual (rendered output).
Outputs
- A prompt artifact with the 7 sections in order: Persona, Context, Constraints, Toolset, Output Schema, Examples, Anti-patterns.
- A short rationale comment at the top documenting why each section was included.
- A passing run under
verification-before-donewith all 5 axes captured.
Failure modes
- Skipping the Anti-patterns section (the model falls into known failure modes with no corrective action).
- Writing Constraints as prose instead of bullet points (the model ignores soft prose).
- Writing Output Schema without a worked example (the model invents a slightly different shape).
- Persona written as "You are a helpful assistant" (no scope, no differentiation).
- Mixing multiple personas in one prompt (the model averages them and produces mush).
Verification checklist
- All 7 sections present and in order.
- Persona states scope in one sentence, not a role-play.
- Context lists inputs and assumptions as bullets, not prose.
- Constraints distinguish hard limits from soft preferences.
- Toolset lists tool names, order, and guard rails.
- Output Schema includes a worked example.
- Examples section has ≥ 1 positive and ≥ 1 negative example.
- Anti-patterns section has ≥ 3 concrete failure modes with corrective actions.
- Prompt verified under
verification-before-done5-axis framework.
Related skills
skills/meta/write-reusable-skill/SKILL.md— author skill files (the sister skill to this one for prompts)skills/core/clarify-before-code/SKILL.md— restate goal + assumptions before authoringskills/core/grill-user-before-building/SKILL.md— interview loop until 95% confidence
Attribution
Inspired by RohitG00/awesome-claude-code-toolkit (Apache-2.0). Adapted in original wording with Vibe Coding OS-specific 5-axis verification.
See also
templates/prompt-template-7-section.md— drop-in 7-section prompt template.commands/vibe-prompt-architect.md— companion command that drives the 7-section authoring workflow interactively.
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