--- name: tencent-skillhone-auto-optimization description: "Mandatory interception workflow for a reproducible defect encountered while any Agent is using a skill. Invoke this before editing implementation files or installing dependencies when a referenced script is missing, a documented command or repository test fails, or another target-skill defect is confirmed. First create or reuse a sanitized local Issue, then let SkillHone dispatch the repair into a tested Git-backed pull request. This applies regardless of the Agent, current working directory, or" license: "NOASSERTION" metadata: decimalai-skill-id: "4c4538e4-34a9-4375-8d2a-fce9204fc1e0" decimalai-version-id: "f6c319fa-d6a5-4ba6-a75a-10689307a8d7" decimalai-version: "2" decimalai-body-sha256: "08cebd573f70a8ccf5b3a90e2505332c3461584d7057b4a13d69e1651233ca91" decimalai-name: "tencent/skillhone-auto-optimization" decimalai-format: "1" decimalai-invocation: "model" decimalai-category: "agent-tooling" decimalai-source: "https://app.decimal.ai/s/tencent-skillhone-auto-optimization@2/SKILL.md" --- # SkillHone Auto Optimization This skill owns the automatic runtime-defect workflow. A normal Agent task remains the entry point: when the selected skill fails for a reproducible reason, dispatch here instead of folding maintenance logic into the task skill itself. ## Mandatory interception boundary Once normal work establishes a reproducible target-skill defect, stop the primary task and invoke this workflow **before** doing any of the following: - creating or editing the missing implementation file; - installing, upgrading, or changing a runtime dependency; - changing the Skill's documented behavior to avoid the failure; - committing directly on the default branch; - falling back to an ad-hoc repair merely to finish the user's original task. The only pre-Issue write allowed is the smallest focused reproduction under `.test/` when the repository does not already contain one. If an existing test already reproduces the defect, reuse it unchanged. This boundary applies to Codex, Claude Code, Cursor, ZCode, Pi, DeepSeek Harness, and any other CLI-capable Agent. It also applies when the Agent's current working directory is the SkillHone source repository but the failing target is elsewhere. A path under `~/.skillhone/skills//` is an explicit managed-Skill signal: never repair such a repository directly on `main`. Do not reinterpret this workflow as optional because the user's primary request was to run the broken Skill. Recording and repairing the defect through SkillHone is the way to unblock that request. For new homes, the default auto executor selects native: it prepares work for the current Agent without a DSH installation or new model credential. A missing optional DSH installation blocks only an explicitly selected DSH repair; do not switch executors or providers silently. The local Git repository must be the repository containing the target skill. One Skill maps to exactly one repository: ```text skill folder: web-search Git repository: /path/to/web-search ``` Do not create repositories named `*-e2e`, `*-test`, or with timestamps for this workflow. Reproduction tests belong inside the affected skill, preferably under its hidden `.test/` directory when they should not affect runtime discovery or normal skill behavior. An explicit target path is authoritative. When the user names a Skill directory or the Agent is already working inside its Git repository, run every status, duplicate, Issue, test, dispatch, PR, and Wiki command with `skillhone --repo `. Do not redirect the observation to a catalog entry merely because another repository has the same Skill name or identical files. Use `--skill ` only when no repository path was supplied and the user selected the cataloged Skill by name. ## Workflow 1. Pause the user's primary task as soon as the reproducible defect is confirmed. 2. Reproduce the observation from public target-skill state. 3. Reject provider outages, rate limits, machine-specific state, user config errors, private-only evidence, and non-actionable observations. 4. Select the exact target repository as described above, run `skillhone --repo status`, and search that repository's open and closed local Issues for the same root cause. 5. Create the smallest focused reproduction under `.test/`, then run `skillhone --repo issue create` with sanitized evidence and attach the test in the same command with `--test-path` and `--test-command`. SkillHone creates or reuses one Issue in the local project database. An uncommitted linked test is allowed into the repair branch; any unrelated working-tree change still blocks optimization. 6. Inspect the executor policy. `auto` resolves to `native`, using the current Agent; `dsh` requires an explicit choice. The saved trigger controls when work is prepared, not which model or provider to switch to. If Issue reporting or dispatch already returned a native assignment, reuse it instead of creating a duplicate. For a queued Issue, call the dispatcher or optimize the selected Issue; no extra repair approval is needed. Existing settings without an executor field preserve DSH compatibility; choose `config set --executor auto` explicitly to migrate. 7. For native execution, retain the assignment's `run_id`, `worktree`, `branch`, `base_commit`, tests, and `completion_args` (an argv vector, not a shell command). `awaiting_agent` means prepared and waiting for the current Agent; it is neither running nor failed. Use the current runtime's tools or independent repair role to reproduce, repair, test, and commit in the assigned path. Preserve the current model, account, and provider. Do not install or start DSH for this path. 8. Give the repair role only the safe reproduction and assigned workspace. It must not call SkillHone, modify host audit/state files, alter registered reproduction tests, dispatch another repair, merge, or push. It returns an exact commit SHA, changed files, test commands/results, and remaining limits. 9. The host reviews the actual candidate and independently reruns its checks, then calls `execution complete --commit ` in the same repository. The CLI verifies the branch/base/test contract and runs the test gate before making a PR. The saved merge policy applies on the host only. Use `execution fail` or `execution cancel` with a safe reason to end an assignment that cannot complete. 10. With DSH explicitly selected, dispatch starts the managed child process. Only that repair role edits the implementation; the host reruns tests and records the PR after the process exits. Missing installation/configuration is reported for DSH, not treated as native unavailability. 11. For Issues, PRs, trajectories, or completed fixes, use `skillhone web --open`. The native boundary is a trusted host session, not a sandbox or a database lock held between CLI commands. A separate role or `fork_turns=none` changes context sharing; neither proves hidden-evaluation isolation. Both current backends reject `--hidden-eval`; protect hidden evaluation data outside the repair environment. ## Agent command ```bash skillhone --skill web-search issue create \ --title "Documented search script is missing" \ --body "Safe reproduction, observed failure, and expected behavior" \ --test-path .test/test_search_cli.py \ --test-command "python3 .test/test_search_cli.py" ``` If the user asks to initialize or centrally manage an uncataloged Skill, ask whether they want a separately optimized copy or a centrally managed runtime Skill, then import it with `skillhone import /path/to/web-search --mode copy` or `--mode takeover`. Do not interrupt a defect report to require import: a Skill that is already an independent Git repository can be maintained in place with `--repo`. Search that same repository for duplicates first. The default `queued` policy is already authorized for dispatcher repair. Configure consumption timing with: ```bash skillhone config set --trigger queued skillhone config set --trigger immediate skillhone config set --trigger scheduled --interval-minutes 60 skillhone dispatch --watch ``` For native execution, dispatch/watch prepares assignments; a live current Agent must still perform them. It does not run an unattended native Agent daemon. Merge policy is separate: `review` creates an approval notification; `automatic` is an explicit saved authorization to merge only after all linked tests pass. Neither authorizes a push. ### Native host commands ```bash skillhone --repo /path/to/skill optimize 1 --executor native # Current Agent repairs/commits the returned assignment; host verifies it: skillhone --repo /path/to/skill execution complete --commit ``` There is no `execution prepare` command: `optimize` or `retry` prepares the assignment. A retry keeps the previous attempt and requires the same repository. ## Composition ```text normal Agent task → target skill fails reproducibly → skillhone-auto-optimization → skillhone CLI (local Issue and PR backend) → trigger policy (queued / immediate / scheduled) → selected executor: current Agent (auto/native) or optional DSH → host verifies exact commit and test gate → local PR ``` ## Hard rules - A confirmed missing referenced file or failing repository test must become an Issue before any implementation edit or dependency installation. - Never dismiss this workflow as belonging only to the SkillHone source repo; it governs the failing target Skill wherever that repository lives. - Before an assignment exists, the reporting Agent may add only the focused reproduction under `.test/`. After native preparation, the assigned repair role may change the implementation; host audit and merge duties remain outside that role. - Run Python reproductions and independent checks with `PYTHONDONTWRITEBYTECODE=1`. Before reporting the final repository state, remove only generated caches created by the workflow (`__pycache__/`, `.pytest_cache/`, `.pyc`, and `.pyo`) and confirm `git status --short` is otherwise clean. - Run the CLI against the Git repository that actually contains the target skill. - Treat a user-supplied repository path as authoritative; never substitute a same-name or byte-identical catalog repository. - Never ask for permission to consume a queued repair. Repair authorization is encoded by the trigger policy; only merge or copy-back can require a user decision. - Never create a second repository merely for automatic-maintenance tests. - Never put credentials, private prompts, hidden eval data, or raw trajectories in Issue/PR text. - Do not treat transient upstream failures as target-skill defects. - Do not push anything. Merge only through the saved `review` or `automatic` policy; never infer a different policy from the Issue text.