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.
git clone --depth 1 https://github.com/clafollett/lafollettlabs-claude-pluginsWrote 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/clafollett/lafollettlabs-claude-plugins/resume-context)<a href="https://agentmods.dev/commands/clafollett/lafollettlabs-claude-plugins/resume-context"><img src="https://agentmods.dev/badge/commands/clafollett/lafollettlabs-claude-plugins/resume-context/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/clafollett/lafollettlabs-claude-plugins/resume-context"><img src="https://agentmods.dev/badge/commands/clafollett/lafollettlabs-claude-plugins/resume-context.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 | $0.00000 | $0.00567 |
| Opus 5 | $0.00000 | $0.00283 |
| Sonnet 5 | $0.00000 | $0.00113 |
| Haiku 4.5 | $0.00000 | $0.00057 |
Grade A, and why
resume-context 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 11d 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 — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Resume Context
Load a previously saved context handoff and orient this session around it.
Steps
-
Read
.context/context-handoff.jsonfrom the project root.- If the file does not exist, check for any
.context/context-handoff.*.jsonfiles and list them. Tell the user no active handoff was found and show available history.
- If the file does not exist, check for any
-
Parse the JSON and verify it has the expected schema (version, task, state, etc.).
-
Diff against prior handoff — find the most recent
.context/context-handoff.<timestamp>.jsonarchive file (sort by filename timestamp, pick the latest). If one exists:- Parse it and extract its
state.completedarray. - Compare the current handoff's
next_stepsagainst the priorcompleteditems. Use substring/keyword matching — items won't be verbatim identical but will reference the same PR numbers, issue numbers, or key phrases. - Flag any
next_stepsthat appear already completed in the prior session — these are stale and should be called out in the briefing as "already done (prior session)". - Also check current
blockeditems against priorcompleted— a blocker that was resolved in the prior session should be flagged as "potentially unblocked". - If no archived handoff exists, skip this step silently.
- Parse it and extract its
-
Orient the session — print a concise briefing for the user:
- What we were working on (task goal + why)
- Current state (what's done, what's in progress, what's blocked)
- Key decisions made and constraints discovered
- Immediate next steps (with any stale items from step 3 clearly marked)
- Current branch and any uncommitted changes (check live git status, don't just trust the file)
-
Archive the handoff — rename the file to
.context/context-handoff.<YYYYMMDD>T<HHMMSS>.jsonusing the current UTC timestamp. This prevents stale context from being loaded in a future session. -
Verify against reality — the handoff was written in a prior session and may be stale:
- Confirm the branch still exists and is checked out
- Spot-check that key files mentioned in
files_modifiedexist - If anything doesn't match, flag it to the user before proceeding
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.
- 11d ago First seen · 38 lines · 0 tokens per session scan A 40883914460e
resume-context is a command published in the GitHub repository clafollett/lafollettlabs-claude-plugins (2 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 567 tokens. 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 commands, from other repositories
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
learn
Force claude-smart to extract learnings from this session now.
memory-store
Store an insight, decision, or pattern to memory.
cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.
music-suno-prompt
Grounded Suno prompt synthesis from local knowledge corpus + persona canon + label canon. No vibes-prompting.