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Prompt

skill-alessiomarcone-agent-fieldbook-prompt · by alessiomarcone

Improves, rewrites, or designs concise prompts with clear outcomes, context, boundaries, output requirements, and verification. Use for direct requests such as “improve this prompt,” for Claude or Codex task formulation, weak-response troubleshooting, or turning a rough objective into a ready-to-run task.

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Install

$ agentstack add skill-alessiomarcone-agent-fieldbook-prompt

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Prompt

Turn a rough request into the shortest prompt that reliably defines the work.

References

  • Read references/ai-fluency-4d-corso.md for Anthropic's Description framework and prompting techniques.
  • Read references/codex-prompting.md for current Codex prompting rules when the target is Codex.
  • Read references/regole-distillate.md only for cross-cutting boundaries and verification.

Procedure

  1. Resolve the target product only when product behavior changes the prompt.
  2. Recover only missing parts that materially affect the result and are supported by the user's request or supplied context:
  • Goal: the result to create or change.
  • Context: relevant sources, files, examples, errors, and prior decisions.
  • Boundaries: what must stay unchanged, what not to invent, and which actions require approval.
  • Output: artifact, format, audience, length, and destination.
  • Done when: observable acceptance checks.
  1. Add examples, role, decomposition, a checklist, or an explicit planning step only when the user requests them or they resolve a concrete ambiguity. Do not add a conventional template merely because it is common for that task type.
  2. Never invent missing scope, numbers, timelines, audiences, deliverables, or acceptance criteria. Preserve a concise request and its approximate length when the user asks for brevity. Use a visible placeholder for a necessary unknown; ask one focused question only when no useful prompt can be produced without the answer.
  3. Add a freshness or source requirement for time-sensitive claims.
  4. Return one ready-to-copy prompt; do not execute it unless requested.

Output contract

Return:

  1. Ready prompt — one copyable block.
  2. Assumptions — only unavoidable assumptions; omit if none.
  3. Why it works — at most two lines.
  4. Verification — the most important check on the result.

When the user explicitly requests a short or simple rewrite, return only the Ready prompt and, if essential, one line of Verification. Do not append a rationale, assumptions section, or follow-up question.

Boundaries

  • Do not inflate a simple request into a long template.
  • Treat explicit brevity as a hard output constraint.
  • Do not turn an unspecified constraint into a convenient assumption.
  • Split unrelated tasks into separate prompts.
  • If the actual need is a skill, project instruction, connector, or subagent, say so.
  • Answer in the user's language.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.