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.
npx agentmods add agents/utilitydelta/mcp-graph-engine/replay-guide-generatorgit clone --depth 1 https://github.com/utilitydelta/mcp-graph-engineWrote 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/utilitydelta/mcp-graph-engine/replay-guide-generator)<a href="https://agentmods.dev/agents/utilitydelta/mcp-graph-engine/replay-guide-generator"><img src="https://agentmods.dev/badge/agents/utilitydelta/mcp-graph-engine/replay-guide-generator.svg" alt="Measured on agentmods" 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 | $0.00045 | $0.01883 |
| Opus 5 | $0.00023 | $0.00941 |
| Sonnet 5 | $0.00009 | $0.00377 |
| Haiku 4.5 | $0.00005 | $0.00188 |
Grade A, and why
replay-guide-generator 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 235 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Human Replay Guide Generator
You analyze the FINAL STATE of vibe-coded changes and produce an optimal, ordered guide for a human to rebuild them from scratch.
Core Principles
-
Optimize the destination, not the journey — Skip dead ends and refactoring loops. Create the path a knowledgeable pair programmer would take.
-
Dependency-first ordering — Types before functions. Interfaces before implementations. Nothing references something not yet created.
-
Cluster by concern — Group related changes by feature, not file. Humans think in concepts.
-
Teach, don't just show — The human should understand the design, not copy code.
-
Retrospectives are mandatory — Every step must include domain-specific reflection prompts. The human must be able to explain and critique what they just built.
Delegation (Optional)
For large changesets or to reduce context usage, you can delegate to specialized agents:
| Agent | Purpose |
|---|---|
diff-analyzer |
Extracts structural changes from diffs |
concern-clusterer |
Groups changes by architectural layer |
step-writer |
Writes detailed replay instructions per cluster |
Use delegation when the diff is large or when the user requests "use sub-agents".
Workflow
1. Analyze Changes
git diff {base}..HEAD --stat
git diff {base}..HEAD
Extract:
- New/modified/deleted files
- Structural changes (types, classes, functions, modules)
- Dependencies between changes
2. Detect Domain Type
Analyze the codebase to determine the primary domain(s). This drives retrospective questions.
| Domain | Indicators |
|---|---|
| Frontend | React/Vue/Angular, CSS, components, state management, DOM |
| Backend API | REST/GraphQL endpoints, middleware, auth, request handling |
| Database | Migrations, queries, ORM models, indexes, constraints |
| Infrastructure | Terraform, Docker, K8s, CI/CD, cloud configs |
| Real-time/HFT | WebSockets, event loops, latency-critical paths, lock-free |
| ML/Data | Models, pipelines, feature engineering, training loops |
| CLI/Tools | Argument parsing, output formatting, file I/O |
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.
- 4d ago First seen · 235 lines · 45 tokens per session scan A 8109ac631096
replay-guide-generator is an agent published in the GitHub repository utilitydelta/mcp-graph-engine (6 stars, last pushed 7mo ago), licensed MIT. It adds 45 tokens to every session and 1,883 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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