hindsight: Skill for Claude Code

.claude/skills/figure/SKILL.md

figure is a skill for Claude Code from vectorize-io/hindsight. It costs 93 tokens per session (2,198 once invoked), scanned A, original, MIT.

A tool for drawing animated diagrams as one self-contained SVG image. SVG is a scalable image format that stays sharp and can be embedded directly in GitHub Markdown, blog posts, and other documents.

In plain words
What is it for?
Use it to show request flows, background jobs, data movement, or feature changes in a README, pull request, issue, or blog post.
Why use it?
It avoids writing SVG by hand or managing video files, scripts, uploads, and build steps for a small explanatory figure.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter.

This is vectorize-io/hindsight's own configuration. It tells Claude Code how to work on hindsight itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything hindsight configures →

About the project

vectorize-io/hindsight is an agent memory system that stores experiences and helps AI agents learn over time instead of only recalling conversation history. It is used by developers adding long-term memory to agents, including coding agents. Catalogue add-ons connect agents to Hindsight and its memory workflows.

vectorize-io/hindsight · 50,509 stars · on GitHub · hindsight.vectorize.io

Reuse

Borrowing it

Nothing to install: this file belongs to vectorize-io/hindsight. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/vectorize-io/hindsight/main/.claude/skills/figure/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/vectorize-io/hindsight

Made for: Claude Code.

Wrote 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.

agentmods badge for figure

README.md
[![agentmods](https://agentmods.dev/badge/skills/vectorize-io/hindsight/figure/github.svg)](https://agentmods.dev/skills/vectorize-io/hindsight/figure)
Your own site
<a href="https://agentmods.dev/skills/vectorize-io/hindsight/figure"><img src="https://agentmods.dev/badge/skills/vectorize-io/hindsight/figure/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.

agentmods 80×15 button for figure

Your own site · 80×15
<a href="https://agentmods.dev/skills/vectorize-io/hindsight/figure"><img src="https://agentmods.dev/badge/skills/vectorize-io/hindsight/figure.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,198 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00093 $0.02198
Opus 5.5 $0.00037 $0.00879
Sonnet 5.5 $0.00019 $0.00440
Haiku 4.5 $0.00009 $0.00220

Measured 9d ago against content hash 7f93dcbfbde2, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

figure 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.

.claude/skills/figure/SKILL.md · 148 lines

How it starts

The opening of the file, as written. The whole thing — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Figure

One animated SVG, no scripts, no upload: it renders and plays anywhere markdown does — GitHub README, PR and issue comments, blog posts, Notion. Sharp at any size, and it follows the reader's light or dark theme.

Figures are Giotto diagrams: one JSON document, the same format the docs site's interactive figures use (hindsight-docs/figures/*.json).

You write the diagram JSON — never SVG. One command renders it. No build, no browser.

1. Write the diagram

Do not save it as a file in the repo. It is an input, not a deliverable — pipe it in (step 2), and the rendered SVG keeps a copy of it for you.

{
  "title": "Retain",
  "speed": 2000,
  "elements": [
    { "id": "root", "type": "group", "children": ["agent", "api", "bank"], "layout": { "direction": "row", "gap": 48 } },
    { "id": "agent", "type": "rectangle", "content": [{ "type": "title", "text": "Your AI Agent" }] },
    { "id": "api", "type": "group", "label": { "title": "Hindsight API" }, "children": ["retain"], "layout": { "direction": "column", "gap": 24 } },
    { "id": "retain", "type": "rectangle", "content": [{ "type": "title", "text": "Retain" }, { "type": "subtitle", "text": "LLM extraction" }] },
    { "id": "bank", "type": "group", "label": { "title": "Memory Bank" }, "children": ["facts", "obs"], "layout": { "direction": "column", "gap": 28 } },
    { "id": "facts", "type": "cylinder", "content": [{ "type": "title", "text": "Facts" }, { "type": "subtitle", "text": "world · experience" }] },
    { "id": "obs", "type": "cylinder", "content": [{ "type": "title", "text": "Observations" }] },
    { "id": "call", "type": "arrow", "route": "curved", "start": { "id": "agent" }, "end": { "id": "retain" }, "label": { "text": "retain()" } },
    { "id": "store", "type": "arrow", "route": "curved", "start": { "id": "retain" }, "end": { "id": "facts" }, "label": { "text": "extract" } },
    { "id": "consolidate", "type": "arrow", "route": "curved", "start": { "id": "facts" }, "end": { "id": "obs" }, "label": { "text": "consolidate" }, "quiet": true }
  ],
  "scenes": [
    {
      "label": "retain()",
      "beats": [
        { "edges": { "edge": "call", "data": "“Alice joined Google in March”" }, "say": "Your agent sends what happened." },
        {
          "edges": "store",
          "show": { "facts": [{ "tag": "world", "tone": "blue", "text": "Alice joined Google", "meta": "Mar 2026", "mark": "new" }] },
          "say": "An LLM pulls out the facts."
        },
        {
          "edges": "consolidate",
          "ms": 2600,
          "show": { "obs": [{ "text": "Alice works at Google", "meta": "2 sources" }] },
          "say": "The worker merges them into one belief."
        }
      ]
    }
  ]
}

Read the full file on GitHub · 148 lines

Changes

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.

  1. 9d ago Changed · -27 lines · +6 tokens per session 7f93dcbfbde2
  2. 22d ago First seen · 175 lines · 87 tokens per session scan A dad0cadba9b3

Subscribe to this mod's changes

figure is a skill published in the GitHub repository vectorize-io/hindsight (50,509 stars, last pushed today), licensed MIT. It adds 93 tokens to every session and 2,198 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-09-25.

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