agent-context-budget

Solid

Use when an agent task needs bounded context packets, checkpoint-aware compaction, a fresh-session primer, or policy-controlled child results without loading raw logs into the primary session.

AI & Automation 26 stars 6 forks Updated 6 days ago MIT

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Quality Score: 82/100

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Skill Content

# 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...

Details

Author
WenyuChiou
Repository
WenyuChiou/agent-collab-skills
Created
4 months ago
Last Updated
6 days ago
Language
Python
License
MIT

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