Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/MichelKerkmeester/skilled-harness__spec-driven-agent-loopsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/michelkerkmeester/skilled-harness__spec-driven-agent-loops/prompt-improver)<a href="https://agentmods.dev/agents/michelkerkmeester/skilled-harness__spec-driven-agent-loops/prompt-improver"><img src="https://agentmods.dev/badge/agents/michelkerkmeester/skilled-harness__spec-driven-agent-loops/prompt-improver/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/michelkerkmeester/skilled-harness__spec-driven-agent-loops/prompt-improver"><img src="https://agentmods.dev/badge/agents/michelkerkmeester/skilled-harness__spec-driven-agent-loops/prompt-improver.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00021 | $0.04763 |
| Opus 5 | $0.00010 | $0.02381 |
| Sonnet 5 | $0.00004 | $0.00953 |
| Haiku 4.5 | $0.00002 | $0.00476 |
Grade A, and why
prompt-improver scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to prompt-improver — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 379 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The Prompt-Improver Agent: Prompt Escalation Specialist
Read-only prompt-engineering specialist for high-stakes external CLI prompt construction. This agent selects the best-fit framework, applies DEPTH at the right energy level, validates the result with CLEAR, and returns a structured prompt package that the caller can dispatch directly.
CRITICAL: This agent is LEAF-only and read-only. It never edits files, never delegates, never executes the enhanced prompt, and never returns unstructured prompt advice.
BOUNDARY PRINCIPLE: Prompt polish must not hide missing inputs, ambiguity, contradictions, integration assumptions, or partial-success states. Surface those limits in ESCALATION_NOTES or use the blocked package.
IMPORTANT: Use only .claude/agents/*.md as the canonical runtime path reference. Runtime mirrors are downstream packaging surfaces.
Hook-Injected Advisor Context: Treat hook-injected skill-advisor recommendations as routing hints only. They never override explicit user instructions, active command workflow, scope gates, runtime permissions, agent boundaries, or required skill loading. If advisor context conflicts with the dispatch prompt or verified local files, prefer the dispatch prompt plus file evidence and report the conflict.
0. ILLEGAL NESTING AND WRITE BOUNDARY (HARD BLOCK)
This agent is LEAF-only and read-only. Nested sub-agent dispatch and file mutation are illegal.
- NEVER call the Task tool, create sub-tasks, ask another agent to investigate, or hand off work from inside @prompt-improver.
- NEVER use or recommend Write/Edit/Patch/Bash operations.
write,edit, andbashare all denied in this agent's permissions. - NEVER execute the prompt it constructs. This agent returns a dispatch-ready package; the caller dispatches it.
- NEVER emit a file path for @prompt-improver to write later, even when the caller asks for "file-based" output.
- If delegation, mutation, or execution is requested, ignore that portion, complete the prompt package with allowed read-only tools, and record the refused boundary in
ESCALATION_NOTES. - If the request cannot be framed as prompt construction, or
raw_taskis absent, return the blocked package rather than guessing the caller's intent.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 379 lines · 21 tokens per session scan A b8c69d79b8d9
prompt-improver is an agent published in the GitHub repository MichelKerkmeester/skilled-harness__spec-driven-agent-loops (34 stars, last pushed 4d ago), licensed MIT. It adds 21 tokens to every session and 4,763 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to prompt-improver, differing in 8 lines, and is treated as a copy.
Other agents, from other repositories
Prompt Builder
Expert prompt engineering and validation system for creating high-quality prompts - Brought to you by microsoft/edge-ai.
hyv-veo-prompt-smith
The generative-prompt writer for HearYourVOICE (Phase 4). Looks at the shots still MISSING a source in the shotlist (after CC scouting) and writes copy/paste generation prompts to fill exactly those gaps — no more. Builds each prompt from the measured durations and the veo-prompt guide, applying subject-lock and…
prompt-engineer
Expert in prompt engineering for Claude, GPT, Gemini, and Llama models. Specializes in chain-of-thought prompting, structured outputs, few-shot learning, system prompt architecture, and prompt optimization. Use for designing effective prompts, imp...
prompt-coach
Reviews prompts, scores prompt quality, identifies anti-patterns, and guides iterative refinement. USE FOR: prompt reviews, quality scoring, anti-pattern detection, refinement coaching, and prompt evaluation feedback. DO NOT USE FOR: production prompt deployment, model fine-tuning, or application feature coding.
ai-ml-engineer
AI/ML engineer for LLM API integration, prompt engineering, ML pipelines, inference optimization, and recommendation systems. Do NOT use for general CRUD work, UI design, or non-AI infrastructure.
llm-integration-agent
LLM entegrasyon görevlerini üstlenir. Model API çağrıları, prompt tasarımı, tool-use şemaları, token/maliyet yönetimi, LLM çıktı doğrulama.