Borrowing it
Nothing to install: this file belongs to davidmatousek/tachi. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/davidmatousek/tachi/main/.claude/commands/tachi.infographic.mdgit clone --depth 1 https://github.com/davidmatousek/tachiWrote 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/davidmatousek/tachi/tachi.infographic)<a href="https://agentmods.dev/commands/davidmatousek/tachi/tachi.infographic"><img src="https://agentmods.dev/badge/commands/davidmatousek/tachi/tachi.infographic/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/commands/davidmatousek/tachi/tachi.infographic"><img src="https://agentmods.dev/badge/commands/davidmatousek/tachi/tachi.infographic.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 | $0.00044 | $0.03178 |
| Opus 5 | $0.00022 | $0.01589 |
| Sonnet 5 | $0.00009 | $0.00636 |
| Haiku 4.5 | $0.00004 | $0.00318 |
Grade A, and why
tachi.infographic 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 9d 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 — 268 lines — stays where its author put it; the contents beside it link to each section on GitHub.
User Input
$ARGUMENTS
Consider user input before proceeding (if not empty).
Step 0: Parse Arguments
-
If
$ARGUMENTScontains--template <value>:- Set
templateto the specified value - Valid values:
baseball-card,system-architecture,risk-funnel,maestro-stack,maestro-heatmap,executive-architecture,all,maestro,corporate-white,exec - If value is
corporate-white: resolve alias tobaseball-card - If value is
exec: resolve alias toexecutive-architecture - If value is
maestro: expand shorthand to["maestro-stack", "maestro-heatmap"]— generate both sequentially - If value is not in the valid list, display:
INVALID TEMPLATE: {value} Valid templates: baseball-card, system-architecture, risk-funnel, maestro-stack, maestro-heatmap, executive-architecture, all, maestro Aliases: corporate-white → baseball-card, exec → executive-architecture, maestro → maestro-stack + maestro-heatmap - Halt if invalid.
- Strip
--template <value>from$ARGUMENTS(trim extra whitespace)
- Set
-
Default:
template = "all" -
If
$ARGUMENTScontains--output-dir <path>:- Set
output_dirto the specified path - Strip
--output-dir <path>from$ARGUMENTS(trim extra whitespace)
- Set
-
Default:
output_dir = null(resolved in Step 1 based on data source location) -
Remaining
$ARGUMENTSis treated as the explicit data source path. -
Default:
data_source_path = null(auto-detect in Step 1)
Overview
Single-command entry point for tachi threat infographic generation — the visual layer in the pipeline: /threat-model -> /risk-score -> /infographic. Auto-detects the richest available data source, invokes the infographic agent in a fresh context, and produces specification files with optional Gemini-generated images.
Flow: Parse -> Validate -> Generate -> Report
Output suite (per template):
threat-{template-name}-spec.md— structured infographic specification (6 sections perschemas/infographic.yaml)threat-{template-name}.jpg— presentation-ready image (only when GEMINI_API_KEY available and API succeeds)
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.
- 9d ago First seen · 268 lines · 44 tokens per session scan A 06ebc1db2f6a
tachi.infographic is a command published in the GitHub repository davidmatousek/tachi (91 stars, last pushed 27d ago), licensed Apache-2.0. It adds 44 tokens to every session and 3,178 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 2026-08-30.
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