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 commands/luanmorenommaciel/agentspec/generate-visual-plangit clone --depth 1 https://github.com/luanmorenommaciel/agentspecWrote 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/commands/luanmorenommaciel/agentspec/generate-visual-plan)<a href="https://agentmods.dev/commands/luanmorenommaciel/agentspec/generate-visual-plan"><img src="https://agentmods.dev/badge/commands/luanmorenommaciel/agentspec/generate-visual-plan.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 5.1 | $0.00020 | $0.01444 |
| Opus 5 | $0.00010 | $0.00722 |
| Sonnet 5 | $0.00004 | $0.00289 |
| Haiku 4.5 | $0.00002 | $0.00144 |
Grade A, and why
generate-visual-plan 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.
This is a copy
100% identical to generate-visual-plan — 38 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Load the visual-explainer skill, then generate a comprehensive visual implementation plan for $@ as a self-contained HTML page.
Follow the visual-explainer skill workflow. Read the reference template, CSS patterns, and mermaid theming references before generating. Use an editorial or blueprint aesthetic, but vary fonts and palette from previous diagrams.
Data gathering phase — understand the context before designing:
-
Parse the feature request. Extract:
- The core problem being solved
- Desired user-facing behavior
- Any constraints or requirements mentioned
- Scope boundaries (what's explicitly out of scope)
-
Read the relevant codebase. Identify:
- Files that will need modification
- Existing patterns to follow (code style, architecture, naming conventions)
- Related functionality that the feature should integrate with
- Types, interfaces, and APIs the feature must conform to
-
Understand the extension points. Look for:
- Hook points, event systems, or plugin architectures
- Configuration options or flags
- Public APIs that might need extension
- Test patterns used in the codebase
-
Check for prior art. Search for:
- Similar features already implemented
- Related issues or discussions
- Existing code that can be reused or extended
Design phase — work through the implementation before writing HTML:
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State design. What new state variables are needed? What existing state is affected? Draw the state machine if behavior has multiple modes.
-
API design. What commands, functions, or endpoints are added? What are the signatures? What are the error cases?
-
Integration design. How does this feature interact with existing functionality? What hooks or events are involved?
-
Edge cases. Walk through unusual scenarios: concurrent operations, error conditions, boundary values, user mistakes.
Verification checkpoint — before generating HTML, produce a structured fact sheet:
- Every state variable (new and modified) with its type and purpose
- Every function/command/API with its signature
- Every file that needs modification with the specific changes
- Every edge case with expected behavior
- Every assumption about the codebase that the plan relies on Verify each against the code. If something cannot be verified, mark it as uncertain. This fact sheet is your source of truth during HTML generation.
Diagram structure — the page should include:
-
Header — feature name, one-line description, scope summary. Visual treatment: use a distinctive header with monospace label ("Feature Plan", "Implementation Spec", etc.), large italic title, and muted subtitle. Set the tone for the page.
-
The Problem — side-by-side comparison panels showing current behavior vs. desired behavior. Use concrete examples, not abstract descriptions. Show what the user experiences or what the code does, step by step. Visual treatment: two-column grid with rose-tinted "Before" header and sage-tinted "After" header. Numbered flow steps with arrows between them.
-
State Machine — Mermaid flowchart or stateDiagram showing the states and transitions. Label edges with the triggers (commands, events, conditions). Wrap in
.mermaid-wrapwith zoom controls (+/−/reset/expand) and click-to-expand. Useflowchart TDinstead ofstateDiagram-v2if labels need special characters like colons or parentheses. Add explanatory caption below the diagram. -
State Variables — card grid showing new state and existing state (if modified). Use code blocks with proper
white-space: pre-wrap. Visual treatment: two cards side-by-side, elevated depth, monospace labels. -
Modified Functions — for each function that needs changes, show:
- Function name and file path
- Key code snippet (not full implementation — 10-20 lines showing the pattern)
- Explanation of what changed and why Visual treatment: file path as monospace dim text above code block, code in recessed card with accent-dim background.
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 · 108 lines · 20 tokens per session scan A 1988ae78139f
generate-visual-plan is a command published in the GitHub repository luanmorenommaciel/agentspec (245 stars, last pushed 3d ago), licensed MIT. It adds 20 tokens to every session and 1,444 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 generate-visual-plan, differing in 38 lines, and is treated as a copy.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
constitution
Create or update the project constitution from interactive or provided principle inputs.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.