agentleFS
YehudaFrankelYehudaFrankel/clankbrain/.claude/skills/act/SKILL.md

act

Skill16 starsChanged 7 months agoMITView on GitHub

Reads recent session context, infers what you were working on, and proposes the specific next action. Use when resuming after a break, or say "act" / "what should we do next" / "pick up where we left off". Executes immediately on confirmation.

4 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

8 rules. 0 are common, 6 are distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 3 edited versions we read keep these.

  • 6

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Read all three sources at once:

    line 28
  2. Distinctive:

    If user says yes / go / do it:

    line 77
  3. Distinctive:

    No re-asking, no re-summarizing

    line 79
  4. Very specific:

    After completion, update [MEM]/todo.md (check off or add follow-up) and [MEM]/session_journal.md

    line 80
  5. Distinctive:

    If user says skip:

    line 82
  6. Distinctive:

    If user says "show me the full context":

    line 86
  7. Distinctive:

    Never propose more than one action at a time — focus wins over completeness

    line 93
  8. Very specific:

    If context is genuinely ambiguous (no journal entries, empty todo, silent STATUS.md), say so and ask what to work on — act cannot invent …

    line 94

“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Skill: act

Description

Reads the last session journal entries, open todos, and active plans to infer current intent — then proposes and executes the single most useful next action without being asked.

Trigger phrases:

  • "act"
  • "what should we do next"
  • "pick up where we left off"
  • "what were we doing"
  • "continue"
  • "resume"
  • (also fires automatically at Start Session if there are open High-priority todos)

Steps

Step 1 — Read context (parallel)

Read all three sources at once:

  1. [MEM]/session_journal.md — last 40 lines (recent session summaries)
  2. [MEM]/todo.md — full file (High/Medium priorities only)
  3. [MEM]/plans/ — list open (non-archived) plan files, read the most recently modified one
Read([MEM]/session_journal.md, offset=last 40 lines)
Read([MEM]/todo.md)
Glob([MEM]/plans/*.md, excluding plans/archive/)

Step 2 — Infer intent

From the context read, identify:

  • What was being built/fixed — look for the last task mentioned in session_journal.md
  • What's blocked or open — todos marked [ ] with High priority
  • What plan is active — any plan file with Status: In Progress or Status: Draft

Rank candidates:

  1. An in-progress plan with an identified next step
  2. A High-priority open todo
  3. The last thing mentioned in session_journal.md

Step 3 — Propose one specific action

State exactly what you propose to do. Be specific — not "continue the feature" but:

"Last session we finished the Java method for adminSendIntroEmail but hadn't wired the HFmtWebservice endpoint yet. I'll add the routing line and test it now."

Or:

"Your todo.md has one High-priority open item: 'Fix session tab scroll position reset on mobile'. I'll investigate the CSS/JS cause now."

Format:

## Picking up

**Last context:** [1 sentence from session_journal]
**Open item:** [specific todo or plan step]

**Proposed action:** [exactly what I'll do in the next 2 minutes]

Go? (yes / skip / show me the full context)

Step 4 — Execute on confirmation

If user says yes / go / do it:

  • Execute the proposed action immediately
  • No re-asking, no re-summarizing
  • After completion, update [MEM]/todo.md (check off or add follow-up) and [MEM]/session_journal.md

If user says skip:

  • Show the next candidate from the ranked list
  • Repeat step 3

If user says "show me the full context":

  • Print the relevant section from session_journal.md + the matched todo/plan

Notes

  • Never propose more than one action at a time — focus wins over completeness
  • If context is genuinely ambiguous (no journal entries, empty todo, silent STATUS.md), say so and ask what to work on — act cannot invent intent from nothing; it surfaces what's already been decided
  • This skill is intentionally opinionated — it picks one thing and drives it
  • Pairs with search-memory when the proposed action needs prior-art research first
  • "act" on Clankbrain kit tasks = look at D:\claude-memory-starter changes
  • "act" on webapps tasks = look at the TicTacWisdom/InfoGrasp codebase

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.