agentleFS
YehudaFrankelYehudaFrankel/clankbrain/.claude/skills/smart-resume/SKILL.md

smart-resume

Skill16 starsChanged 7 months agoMITView on GitHub

Reads STATUS.md, todo.md, and recent memory to identify what was in progress, then proposes and executes the specific next step. Use when resuming work after a break, or say "smart resume" / "pick up where we left off" / "what were we working on" / "what's next".

The file

We split this skill into the rules it gives an agent

8 rules. About 0 are common, 7 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈7

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    If STATUS.md or todo references a specific file being edited, check its current state:

    line 35
  2. Distinctive:

    If user says yes / go / do it:

    line 64
  3. Very specific:

    Follow plan-before-edit.md — show plan, wait for approval, then edit

    line 65
  4. Distinctive:

    After edit: update STATUS.md + todo.md

    line 66
  5. Distinctive:

    If user says skip:

    line 68
  6. Distinctive:

    If user says "show me all open items":

    line 71
  7. Distinctive:

    Always follow plan-before-edit.md before touching any code

    line 78
  8. Distinctive:

    If no clear next step exists, say so: "No open work found — what should we work on?"

    line 80

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “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: smart-resume

Description

Reads recent work context — STATUS.md, todo, open plans — to infer what's in progress and propose the single most useful next action. Executes on confirmation.

Trigger phrases:

  • "smart resume"
  • "pick up where we left off"
  • "what were we working on"
  • "what's next"
  • "continue"
  • "resume"

Steps

Step 1 — Read context (parallel reads)

Simultaneously read:

  1. [MEM]/STATUS.md — session number + last change summary
  2. [MEM]/todo.md — open items (High/Medium priority)
  3. [MEM]/plans/ — glob for non-archived plan files; read the most recently modified

Step 2 — Check for in-flight work

If STATUS.md or todo references a specific file being edited, check its current state:

  • Grep for // TODO or // IN PROGRESS markers in the mentioned file (use offset+limit — never read whole large files)

Step 3 — Infer the single most important next action

Rank candidates by specificity:

  1. A plan file with Status: In Progress that has an identified next step
  2. A High-priority todo item marked [ ]
  3. The last change summary from STATUS.md — what's the natural follow-on?
  4. A Medium-priority todo

Step 4 — Propose with full context

## Smart Resume — Session [N]

**Last session:** [STATUS.md summary]
**Open work:** [specific todo or plan step]

**Proposed next step:**
[Specific action — e.g., "Add the routing line for appXxx in routes.js around line 200"]

**Files involved:** [list]

Go? (yes / skip / show me all open items)

Step 5 — Execute on confirmation

If user says yes / go / do it:

  • Follow plan-before-edit.md — show plan, wait for approval, then edit
  • After edit: update STATUS.md + todo.md

If user says skip:

  • Show next candidate from ranked list

If user says "show me all open items":

  • Print the full todo.md High+Medium sections + all open plan files

Notes

  • Always follow plan-before-edit.md before touching any code
  • This skill reads context only in Steps 1-2 — no edits until Step 5 after explicit confirmation
  • If no clear next step exists, say so: "No open work found — what should we work on?"

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.