SuperAPI AI Directory

agent-context-budget

Agents & models

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Updated 10-16 05:53

About this skill

agent-context-budget

Prepare bounded context for a task without inventing a second budget source. Numeric limits come from the policy referenced by the current TaskCheckpoint. The public contract and commands are documented in ../../docs/public-harness-contract.md.

Use this skill for

  • A task that may spawn a delegated executor or reviewer.
  • A transcript approaching its configured checkpoint boundary.
  • A fresh session that needs a compact, evidence-linked primer.
  • Results or logs that are too large for the primary-agent context.

Do not use it to summarize away unresolved failures, human decisions, raw scientific evidence, or security findings.

Inputs

  • Goal and task id.
  • Readable agent policy.
  • Current TaskCheckpoint.
  • Evidence and artifact paths needed by the next role.
  • Optional existing .coord/plan.yml and approved memory events.

If the policy is configured but unreadable, stop. If the optional agent-collab-harness package is unavailable, do not start an autonomous loop or child spawn; prepare the packet for human-controlled execution instead.

Workflow

  1. Validate policy and checkpoint:

    agent-collab policy validate --policy <policy-ref> --json
    agent-collab checkpoint validate --checkpoint <checkpoint-ref> --json
    
  2. Record current observed metrics in the checkpoint. Do not estimate a lower number to fit the policy.

  3. Run policy evaluation before a child spawn:

    agent-collab policy evaluate \
      --policy <policy-ref> \
      --checkpoint <checkpoint-ref> \
      --json
    
  4. Obey the result:

    • continue and spawn_allowed=true: create the bounded task packet.
    • checkpoint: write a checkpoint/primer. A v2 slice with auto_continue advances atomically and resumes under the same goal; v1 returns control. For v2 scope=action with context_compaction_required, perform local context maintenance without asking for renewed approval: preserve full artifacts, acceptance evidence, failures, and authorization; build a smaller linked packet or use native compaction, record measured sizes, then re-evaluate. Do not spawn or advance a slice while this context gate is pending.
    • stop or spawn_allowed=false: do not spawn. Respect v2 decision scope; exhaustion of one action does not prohibit safe primary-agent diagnosis.
  5. Put only decision-relevant material in the packet:

    • goal and acceptance contract
    • explicit files and tools in scope
    • direct evidence references
    • current recorded human decisions
    • relevant interfaces or schemas
  6. Keep raw logs and complete artifacts at paths. Include a short failure excerpt only when it is needed to diagnose the next action.

  7. After a result returns, update observed metrics and evaluate again.

Outputs

  • .coord/context_.md: round-specific packet plan.
  • .coord/session_primer.md: bounded fresh-session digest.
  • Updated TaskCheckpoint at the plan's checkpoint_ref.

These are scratch artifacts by default. Promote a checkpoint snapshot only when the repository explicitly needs it for resume, shipping, or acceptance evidence. Agent boundaries do not imply commits.

Packet shape

# Context packet — <task id>

Policy
- policy_ref: <path>
- policy_hash: <sha256>
- checkpoint_ref: <path>

Goal
<one bounded objective>

Recorded decisions
- <gate / actor / decision / action hash>

Evidence
- <path or stable source locator>

Scope
- may read: <paths>
- may write: <paths>
- must not touch: <paths>

Acceptance
- <runnable check>

Return contract
- concise summary
- files changed
- tests run
- risks and blockers
- raw logs by path only

Invariants

  • Policy values have one machine-readable source.
  • v2 slice counters reset only through checkpoint advance; goal totals and accepted evidence never reset. Retain the stricter explicit native/host limit.
  • Reserve child capacity for required independent review. Completed children release active concurrency; the host's actual capacity also limits spawning.
  • No silent retry, model switch, context discard, or result truncation.
  • Compaction changes active context, not cumulative usage or failure history. If safe compaction is unavailable, report that limitation, not a generic request to continue. Never clear an ambiguous legacy blocker automatically.
  • Missing evidence is reported as missing, not summarized as success.
  • A decline, cancellation, timeout, error, or null result remains non-success.
  • Recall systems may suggest context; they do not override repository state or recorded human decisions.