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 skills add memi-design/design-skills --skill agent-session-checkpointsgit clone --depth 1 https://github.com/memi-design/design-skillsWrote 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/skills/memi-design/design-skills/agent-session-checkpoints)<a href="https://agentmods.dev/skills/memi-design/design-skills/agent-session-checkpoints"><img src="https://agentmods.dev/badge/skills/memi-design/design-skills/agent-session-checkpoints/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/skills/memi-design/design-skills/agent-session-checkpoints"><img src="https://agentmods.dev/badge/skills/memi-design/design-skills/agent-session-checkpoints.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 | $0.00020 | $0.00212 |
| Opus 5.5 | $0.00008 | $0.00085 |
| Sonnet 5.5 | $0.00004 | $0.00042 |
| Haiku 4.5 | $0.00002 | $0.00021 |
Grade A, and why
agent-session-checkpoints 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 1mo 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.
What it actually says
Agent Session Checkpoints
Capture restartable agent sessions with checkpoints, rollback notes, and resume metadata.
When to Use
Use this Note when a Memoire or Studio run needs checkpoint agent run, rollback session, resume session, session cleanup.
Workflow
- Create a checkpoint before broad edits, dependency updates, generated files, or external mutations.
- Record session id, prompt, harness, cwd, branch, dirty-state summary, and verification command.
- Resume by explicit session id when possible rather than reconstructing context from terminal history.
- On rollback, preserve the failure explanation and exact reverted scope.
- Clean old sessions only after artifacts and useful lessons have been moved into durable memory.
Sources
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 28 lines · 20 tokens per session scan A 911fbc118324
agent-session-checkpoints is a skill published in the GitHub repository memi-design/design-skills (7 stars, last pushed 27d ago), licensed MIT. It adds 20 tokens to every session and 212 once invoked, about $0.0001 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 2026-08-31.
Other skills, from other repositories
accessibility-per-component
Audit one design system component's accessibility against WCAG 2.2 AA: keyboard, screen reader, contrast, focus, ARIA, target size. Trigger: a11y audit, is this accessible, WCAG check, screen reader support, keyboard navigation check. Not for page- or product-wide audits.
figma-variable-audit
Audit Figma variable collections: tier mapping, naming, alias chains, modes, orphans; can fix in place with Figma Console MCP. Triggers: audit my Figma variables, review variable collections, Figma variable health. For token files in code use token-audit.
theme-audit
Audit theme parity: tokens missing or unchanged per theme, component tokens bypassing semantics, contrast within each theme, resolver contexts, theme-switch regressions. Triggers: dark mode audit, theme coverage, brand variant parity. For general token structure use token-audit.
token-audit
Audit how design tokens are defined: tiers, naming, alias chains, raw values, orphans, DTCG readiness. Triggers: audit my tokens, token architecture review, token health check. Not for code consuming tokens (token-compliance), theme parity (theme-audit) or Figma variables (figma-variable-audit).
ai-component-description
Write a six-section prose description (purpose, props, anti-patterns, composition, accessibility, examples) for a Figma component's description field so LLMs read it via MCP. Triggers: describe this component for AI, Figma MCP description. JSON metadata files: use metadata-schema-generator.
cicd-integration
Generate CI pipeline files and check scripts (GitHub Actions, GitLab, CircleCI, Bitbucket) that automate design system checks: token validation, hardcoded values, a11y scans, visual regression, bundle size. Trigger: set up CI, quality gates, automate these checks. Not for running an audit.