agentleFS
paperclipaipaperclipai/paperclip/.agents/skills/create-runner-adapter/SKILL.md

create-runner-adapter

Skill107k starsChanged 7 days agoMITView on GitHub

Add a new harness/provider integration to native Paperclip Runner, from requirements and protocol research through implementation, packaging, and real end-to-end acceptance. Use for new Runner adapters; legacy direct adapter authoring and migration are outside this skill.

We split this skill into the rules it gives an agent

17 rules. About 0 are common, 13 are distinctive, and 4 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈13

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 4

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Use this skill to add a harness to the new, native Paperclip Runner execution system.

    line 12
  2. Distinctive:

    Use its working templates for the release contract, capability inventory, acceptance ledger, and failure record.

    line 19
  3. Distinctive:

    No private chat, task, prior campaign, or separate private repository is required.

    line 22
  4. Very specific:

    If this skill was installed separately, locate the target checkout from the current workspace or git rev-parse --show-toplevel.

    line 25
  5. Distinctive:

    Follow that checkout's AGENTS.md and scoped rules before editing.

    line 28
  6. Distinctive:

    Define a finite release: Read playbook sections 1–3.

    line 32
  7. Distinctive:

    Keep the complete capability inventory separate from the release requirements.

    line 35
  8. Distinctive:

    Investigate the actual harness: Use section 4. Inspect versioned official docs, native source or shipped code, real protocol traffic, and …

    line 36
  9. Very specific:

    Prove one complete slice: Use sections 5–7. Establish exact model and instruction admission, scoped tools and credentials, then complete …

    line 40
  10. Distinctive:

    Complete the promised behavior: Use sections 8–10. Preserve rich events, durable human decisions, callback identity, recovery, …

    line 45
  11. Distinctive:

    Prove delivery: Use section 11. Exercise clean installed packages and the agreed execution environment.

    line 48
  12. Very specific:

    Qualify the release: Use sections 12–15. Begin with deterministic and real dependency checks, then run exact Product E2E cells through …

    line 51
  13. Distinctive:

    Hand off an operable result: Use section 16 and the templates.

    line 55
  14. Distinctive:

    Verify the caller's exact model at the native boundary before the first prompt.

    line 62
  15. Distinctive:

    Stop must reach the owned native work and prevent late callbacks from reviving it.

    line 68
  16. Distinctive:

    Keep campaign evidence, budget history, and candidate/publication state durable across interruptions.

    line 79
  17. Distinctive:

    Keep new guidance shareable: put the complete lesson and reproducible acceptance condition in tracked documentation.

    line 84

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Add a native Runner adapter

Use this skill to add a harness to the new, native Paperclip Runner execution system. Here, adapter means the provider translation and launch integration behind a Runner harness driver. Preserve existing direct adapters and historical records as compatibility constraints; do not route this work through their package-authoring recipe or migrate agents as a side effect.

The complete procedure is the Runner integration playbook. Use its working templates for the release contract, capability inventory, acceptance ledger, and failure record. These repository files contain the decision rules and test criteria themselves. No private chat, task, prior campaign, or separate private repository is required. Source links identify code to inspect, not evidence that a new integration passed.

If this skill was installed separately, locate the target checkout from the current workspace or git rev-parse --show-toplevel. Verify it contains packages/paperclip-runner and tests/runner-e2e; resolve doc/ paths there. Follow that checkout's AGENTS.md and scoped rules before editing.

Work sequence

  1. Define a finite release. Read playbook sections 1–3. Record the user outcome, first environment, supported platforms, setup/auth, required capabilities, selected acceptance model, spending limits, and delivery target. Keep the complete capability inventory separate from the release requirements.
  2. Investigate the actual harness. Use section 4. Inspect versioned official docs, native source or shipped code, real protocol traffic, and account/model behavior. Track every capability through native harness, wrapper, Runner, controller, and UI. Distinguish documented, observed, and qualified support.
  3. Prove one complete slice. Use sections 5–7. Establish exact model and instruction admission, scoped tools and credentials, then complete one real Paperclip task with independently verified output and physical cleanup. Exercise ordinary connect/save/reopen/Test/reconnect in the selected environment; check database constraints and account/model routing as well as driver execution.
  4. Complete the promised behavior. Use sections 8–10. Preserve rich events, durable human decisions, callback identity, recovery, cancellation, and terminal settlement. Keep provider-specific semantics in provider code.
  5. Prove delivery. Use section 11. Exercise clean installed packages and the agreed execution environment; verify the complete runtime closure and immutable image identity. A source checkout or startup probe is insufficient delivery proof.
  6. Qualify the release. Use sections 12–15. Begin with deterministic and real dependency checks, then run exact Product E2E cells through browser/server/DB/ Runner/provider. Section 12 includes a repository-contained test-authoring path. Freeze the candidate and retain original failures, cost coverage, and cleanup.
  7. Hand off an operable result. Use section 16 and the templates. Account for repository checks, exact passing evidence, remaining limits, installation, operation, and rollback. Keep merge, publish, deploy, and canary claims distinct.

Rules that must survive implementation pressure

  • A qualification model is a repeatable test choice, not a product allowlist. Verify the caller's exact model at the native boundary before the first prompt.
  • Instruction transport success is insufficient: bind exact content on create and load, reject missing acknowledgments, and verify resulting behavior.
  • A native question, semantic question, plan, and permission request are distinct contracts. Preserve identity and prove delivery; queued does not mean answered.
  • Same conversation does not establish same process or recoverable pending input. Stop must reach the owned native work and prevent late callbacks from reviving it.
  • A screenshot, model-authored success claim, or green unit suite cannot replace independent file/artifact/state/cleanup checks through the promised user path.
  • Diagnose the first divergence across arguments, transport, files, persistence, and grader before another paid attempt. Preserve the original grade.
  • Changes after a pass require an evidence-impact decision. Old results retain their original runtime, model, environment, and fixture identity.
  • Prove spontaneous native-child loss and bounded shutdown, not only cleanup invoked by a test. Preserve durable expiry for each supported request kind.
  • Establish the concurrency being graded: attached work must overlap finish; a Stop case must reach real pending work before its observation window closes.
  • Keep campaign evidence, budget history, and candidate/publication state durable across interruptions. Reconcile shipping dependencies before final qualification.
  • Preserve legacy behavior through focused regression checks. Legacy authoring, runtime conversion, and migration are not part of adding a native integration.

Keep new guidance shareable: put the complete lesson and reproducible acceptance condition in tracked documentation. Do not substitute personal session links, private task URLs, inaccessible evidence archives, or workstation-specific paths.

Download now (ZIP)

Trending

Steady: 0 new projects took it in the last 4 weeks, none the 4 weeks before.thin data

Week of Aug 30: 0 new projectsWeek of Sep 6: 0 new projectsWeek of Sep 13: 0 new projectsWeek of Sep 20: 0 new projectsWeek of Sep 27: 0 new projectsWeek of Oct 4: 0 new projectsWeek of Oct 11: 0 new projectsWeek of Oct 18: 0 new projects
Aug 2026Sep 2026Oct 2026
New projects taking a version of this file each week, over the 8 weeks our latest run read: only 0 in all, so this is a hint, not a trend.

Who's talking about paperclipai/paperclip

The biggest 5 of 80 mentions linking to the repository that our crawl found. Each line is their own headline.

See all 80

Talked about on GitHub, Bluesky and Hacker News (80 times).

On GitHub · 50

45 more on GitHub

On Bluesky · 25

20 more on Bluesky

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

Reviews can't be read right now.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.