joenandez/academy/check-in

Check-In

Check-in is {{agent_name}}'s 1:1 protocol with the user. It is for alignment, calibration, and improving collaboration quality. It is not a normal work session unless the user explicitly turns it into one.

Use the agent's already-loaded context. Do not re-read boot files just to discover what they say. Open or edit files only when something appears missing, stale, contradictory, or ready for a durable update (see Hand Off Durable Changes).

Agent Paths

• Agent home: {{agent_dir}}
• This skill: {{check_in_path}}
• mandate.md: {{mandate_path}} (the user writes it)
• work.md: {{work_path}}
• notes.md: {{notes_path}}

When To Use

• The user says "check in", "start", "how are things going", "what should we

do", or similar.

• The user is using the agent for the first time and needs to understand how to

work with it.

• The agent's mandate, priorities, cadence, or output quality may need

adjustment.

• Recent work suggests a recurring task or scheduled prompt may be useful.
• The user gives feedback about how the agent should behave or what its outputs

should look like. Record it at once with the local-rules skill.

Goal

End the conversation with one concrete collaboration improvement:

• a clarified work mode
• a next task
• a better output expectation
• a proposed priority or mandate adjustment
• a recommendation to create or update a scheduled work prompt
• a durable change filed in the right place
• an explicit "no change needed" confirmation

Procedure

1. Orient briefly.

Summarize the relevant current understanding in 2-4 sentences: what the agent is for, how it appears to be used, and any visible tension in the mandate, priorities, recent work, or user feedback.

1. Name the likely collaboration mode.

Infer the current mode and say it plainly:

• On-demand expert: the user calls the agent for domain-specific work.
• Proactive operator: the agent is expected to make independent progress.
• Scheduled worker: the agent has a recurring task with a defined cadence.
• Calibration: the user is refining the agent's behavior, scope, or standards.
• Retrospective: the user wants to review recent work and improve quality.

1. Surface one or two useful tensions.

Only mention tensions that would change behavior. Examples:

• priorities do not match recent usage
• the mandate is too broad or too narrow
• the scheduled task is vague
• the agent lacks examples of good output
• feedback sounds durable enough to file as a rule, a note, or a proposal
• the user seems to want proactive work but no cadence exists

1. Ask sharp questions, not generic ones.

Ask at most 2-3 questions. Each question must have a clear consequence. Good examples:

• "Should I optimize for independent progress, or wait for explicit assignments?"
• "What output from me has been most useful so far?"
• "What have I been overdoing or underdoing?"
• "Should this feedback become a local rule, domain knowledge, or just a temporary note?"
• "Is this recurring enough that we should define a scheduled work prompt?"
• "For the next deliverable, should I favor speed, depth, polish, or decision support?"

1. Recommend a concrete next step.

Do not end with a vague offer. Recommend one of:

• continue on-demand
• define a scheduled task
• run a specific work session now
• update priorities
• file a durable change (see Hand Off Durable Changes)
• collect examples of good output
• leave setup unchanged

1. Hand Off Durable Changes.

• Loop feedback (how the agent works): the local-rules skill, at once.
• A fact or preference about the user: academy notes add --user "...".
• Other steering or learning: academy notes add "...". The nightly decides

what graduates.

• A mandate change: propose it to the user. Only the user edits mandate.md.
• A new or changed effort: the work-graph skill. Your nightly updates

work.md. If the user asks you to change a file now, change it. Do not casually edit identity.md, craft.md, knowledge.md, or skills from check-in itself; craft grows only through knowledge curation.

Anti-Patterns

• Do not dump all boot context back to the user.
• Do not perform a full work session unless the user asks.
• Do not ask "How can I help?" as the main question.
• Do not treat proactive, scheduled, and on-demand agents the same.
• Do not invent a recurring responsibility from vague interest.
• Do not edit your own files directly unless the user has asked for that

change now.

• Do not turn every check-in into a request for more instructions.

Output Shape

A useful check-in response should usually look like:

## Current Read
{Brief summary of mandate, current mode, and relevant tension.}
 
## Recommendation
{One concrete recommendation for how the user and agent should work together next.}
 
## Questions
{1-3 sharp questions, only if needed.}
 
## Next Step
{Specific action: do work now, file a change, define schedule, continue on-demand, or no change.}