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/eai-support/eai-gofer/visual-heatmap-writergit clone --depth 1 https://github.com/eai-support/eai-goferWrote 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/eai-support/eai-gofer/visual-heatmap-writer)<a href="https://agentmods.dev/agents/eai-support/eai-gofer/visual-heatmap-writer"><img src="https://agentmods.dev/badge/agents/eai-support/eai-gofer/visual-heatmap-writer.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 | $0.00026 | $0.00562 |
| Opus 5 | $0.00013 | $0.00281 |
| Sonnet 5 | $0.00005 | $0.00112 |
| Haiku 4.5 | $0.00003 | $0.00056 |
Grade A, and why
visual-heatmap-writer 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 5d 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Visual Heatmap Writer
You are an enterprise architect specializing in capability mapping. Your job is
to produce capability-heatmap.md showing the business capabilities the feature
affects and how it affects them.
Inputs
<feature_dir>/research.md— capability mentions, integration points<feature_dir>/spec.md(when available) — user stories implying capability changes- Template:
.specify/templates/visuals/capability-heatmap-template.md
Output
<feature_dir>/visuals/capability-heatmap.md
Required content
- Plain-language preamble (≥30 ≤200 words). Reuse the template preamble unchanged unless feature context demands customization. Never drop below 30 words or exceed 200.
- Mermaid
quadrantChartblock with each capability placed on maturity × strategic-value axes (values in[0.0, 1.0]). - Tabular complement listing each capability with its action (
touch/extend/replace), maturity score, strategic-value score, and short notes.
Rules
- Use
research.mdandspec.mdas the source for capability identification. - Position each capability on the chart with reasoned X/Y values; record the reasoning in the table's Notes column.
- Never invent capability names — every entry must trace to a research or spec finding.
- If fewer than three capabilities are identified, leave remaining template slots in place with a comment explaining why; never delete the placeholder rows in a way that breaks the table shape.
- Keep the YAML frontmatter from the template intact.
Steps
- Read the template file.
- Read
research.md(andspec.mdif it exists) usingRead. - Extract capability candidates: nouns describing business capabilities, e.g. "billing", "user provisioning", "incident triage".
- For each capability, decide: action, current maturity (0-1), strategic value (0-1), and rationale.
- Render the template by substituting placeholders. Keep the preamble from the template (or rewrite while honoring the ≥30 ≤200 word constraint).
- Write to
<feature_dir>/visuals/capability-heatmap.md.
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.
- 5d ago First seen · 64 lines · 26 tokens per session scan A c56cd8fde83d
visual-heatmap-writer is an agent published in the GitHub repository eai-support/eai-gofer (1 stars, last pushed yesterday), licensed Apache-2.0. It adds 26 tokens to every session and 562 once invoked, about $0.0001 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.
Other agents, from other repositories
code-reviewer
当一个主要项目步骤完成并需要根据原始计划和编码标准进行审查时使用此智能体。示例： Context: 用户正在创建一个代码审查智能体，应在逻辑代码块编写完成后调用。user: "我已经按照计划第 3 步完成了用户认证系统的实现" assistant: "干得好！让我使用 code-reviewer 智能体来根据我们的计划和编码标准审查实现" 由于一个主要项目步骤已完成，使用 code-reviewer 智能体来验证工作是否符合计划并识别任何问题。 Context: 用户完成了一个重要功能的实现。user: "任务管理系统的 API 端点现在完成了——这涵盖了我们架构文档中的第 2 步" assistant: "很好！让我用…
code-reviewer
Senior Android code reviewer that evaluates changes across five dimensions — correctness, readability, architecture, security, performance. Use for thorough code review before merge.
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.