sdlc-context-reuse

name	sdlc-context-reuse
description	Build cost-aware context reuse reports for the SDLC Automation Demo by loading AGENTS.md, skills, existing logs, GitHub repo search results, and prior OpenHands conversation memory before broad model work.
triggers	["openhands-context","context reuse","agent memory","token savings","lower cost model"]

Cost-Aware Context Reuse

Use this skill when OpenHands needs to show how an agent avoids rediscovering the same repository, workflow, logs, and prior decisions on every run.

The customer-facing story is: a low-cost scout agent gathers reusable context first, writes a compact handoff report, and only then does the expensive coding or risk-review agent act.

Context Source Order

1. AGENTS.md for durable repo rules, commands, product constraints, and human gates.
2. Repo-local skills for procedural memory: sdlc-story, sdlc-qa, and sdlc-code-review.
3. Existing polished evidence, especially docs/qa-reports/ and curated repo memory.
4. Targeted GitHub repo search for the files and tests relevant to the trigger.
5. Previous agent-run lessons in docs/repo-memory/previous-agent-runs.md.

Workflow

1. Read AGENTS.md and docs/repo-memory/petstore-intelligence.md before broad exploration.
2. Select only the skills relevant to the trigger label or issue type.
3. Run the deterministic context report builder when local tools are available:

python3 scripts/build_context_reuse_report.py \
  --fixture tests/fixtures/github_issue_labeled_context.json \
  --output docs/context-reuse/latest-context-reuse-report.md

4. Use the report as the handoff from the scout phase to build, QA, or review work.
5. Do not add workflow-trigger labels such as openhands-build, openhands-review, or openhands-qa; recommend the next step and let a human apply the label.
6. Update durable memory only when you learned a reusable fact. Keep issue-specific details in PRs, issue comments, or context reports.

Model Routing Policy

• Use no LLM or the lowest-cost model for deterministic parsing, label classification, file search, and log summarization.
• Use a low-cost model for the scout report when summarization is needed.
• Use a coding-capable model only for implementation or plan repair.
• Escalate to a stronger model for security, broad architecture, or ambiguous product decisions.
• Prefer exact command output and checked-in evidence over generating a fresh explanation from scratch.

Report Requirements

A context reuse report must include:

• which durable memory was loaded
• which skills were loaded
• which logs or reports were reused
• which files were found by targeted repo search
• which previous agent runs or conversations were reused
• what broad exploration was skipped
• what model tier should handle each phase
• a rough token/context estimate with a clear caveat that it is illustrative, not billing data

Stop Conditions

Ask for human input if the trigger requires secrets, production mutation, billing/IAM changes, destructive actions, or broad scope that cannot be narrowed from repo-local memory and search.