Model upgrade evaluator
Skill Abhillashjadhav/PM-agent-OS/.claude/skills/model-upgrade-evaluator
Iterate-stage skill: turns a new model release into a re-test plan for current prompts and shelved ideas — every verdict cites a run result, no capability assumed from release notes. Use when a new model version lands — 'new model dropped, what should we re-test', 'worth migrating our prompts?', 'build the upgrade evaluation plan', 're-test our shelved ideas' — or when /pm routes such a request here. Do NOT use to gate an already-decided migration's ship (regression-gatekeeper), for per-task tier routing (model-complexity-router), for release-notes summaries, or for academic benchmarking.From its SKILL.md
npx -y skills add Abhillashjadhav/PM-agent-OS --skill model-upgrade-evaluatorAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
- 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
5.4 KB, ~1.1k tokens by cl100k_base, as published. Nobody here has run it
Model Upgrade Evaluator
Release notes are hypotheses. A new model changes two lists — what might now break (current prompts) and what might now work (shelved ideas) — and both get answered by runs, not by the announcement.
Verification gates (defined first; output is blocked until all pass)
- G1 — Every verdict cites a run: MIGRATE/STAY/RESURRECT/STILL-DEAD verdicts exist only with per-case run evidence (counts, deltas, the failing or passing cases named). Before runs execute, every verdict slot reads
PENDING. Release-note claims appear only as hypotheses-to-test, never as capability facts. - G2 — Kill reasons become resurrection tests: each shelved idea is re-tested against the specific reason it was killed (the historical failing case or its closest reconstruction) — not a fresh demo that avoids the old trap. A resurrection test that doesn't encode the kill reason fails.
- G3 — Budget-honest coverage: the plan ranks runs within the stated budget, names what's cut, and marks unscheduled items
UNTESTED — not a verdict. Claimed coverage beyond scheduled runs fails.
Steps
- Inventory both lists: production prompts with their golden sets (these re-run under regression-gatekeeper rules — fail-class assertions must hold), and the shelved-ideas log with each idea's kill reason stated as a testable condition.
- Convert release-note claims into targeted hypotheses. "Better instruction-following" → which of our golden failures were instruction-following failures? Those cases are the test. A claim that maps to none of our cases gets a note: "no surface to test this on — irrelevant until we have one."
- Design resurrection tests from kill reasons. "Degraded beyond 4 docs" → the historical 5-doc case (or its reconstruction, labeled). "Hallucinated priorities" → the hallucination check on the old triage inputs. The bar for RESURRECT is the old failure passing, not a new demo dazzling.
- Rank within budget: production prompts first (regression risk is live risk), then shelved ideas by value-if-unblocked. State the cut list. An afternoon buys what it buys; the plan says so.
- Pre-commit verdict templates: MIGRATE (goldens ≥ baseline, deltas cited) · STAY (regressions, cases named) · RESURRECT (kill-reason test passes, run cited) · STILL DEAD (run cited) · UNTESTED (explicitly not a verdict). Fill them only from results.
- Gate pass. No filled verdict without its run evidence (G1), every resurrection test encodes its kill reason (G2), coverage matches schedule (G3). Fix and re-run; maximum 2 repair loops, then report the failure.
Output format
UPGRADE EVALUATION: <model version> (budget: one afternoon)
HYPOTHESES FROM RELEASE NOTES (to test, not to trust)
H1 "better instruction-following" → classifier goldens #3,#7,#11 (past IF failures)
H2 "2x context" → multi-doc resurrection test (below)
RE-TEST PLAN (ranked, budget-shaped)
1. summarizer goldens (14) · 2. support-draft (12) · 3. classifier (20)
4. shelved: multi-doc synthesis — resurrection test: the historical 5-doc case
[kill reason: degraded >4 docs] · CUT (budget): auto-triage — UNTESTED
VERDICTS (filled only from runs)
summarizer: PENDING → [after run: MIGRATE — 14/14, fail-class held, rubric +0.4 avg]
multi-doc synthesis: PENDING → [after run: RESURRECT only if the 5-doc case passes; else STILL DEAD, run cited]
auto-triage: UNTESTED — not a verdict; first in queue next budget.
GATE CHECK: G1 pass (0 unrun verdicts) · G2 pass (kill reasons encoded) · G3 pass (cuts named)
Hard rules
- Nothing is assumed from release notes — not capability, not safety, not cost. Notes generate hypotheses; runs generate verdicts.
- Resurrection requires the old failure to pass, on the case (or labeled reconstruction) that killed it. New demos that route around the trap prove nothing.
- UNTESTED is an honest state, never rounded to a verdict in either direction.
- Production re-tests inherit regression-gatekeeper's tripwire: a fail-class golden passing its bad behavior through = the migration is a HOLD for that prompt, whatever the rest says.
Limitations
- The evaluation covers your surface, not the model: a clean sweep means your prompts and cases work, not that the model is better in general.
- Reconstructed kill cases (original inputs lost) are labeled and weaker than originals; verdicts on them say so.
- Cost/latency deltas are part of MIGRATE math only when measured in the runs — pricing-page arithmetic goes to unit-economics-stress-test.
- One release per evaluation; comparing three candidate models is this skill run three times plus a decision the user owns.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.
Gives 0 of the 12 instructions most ship operate skills give in ~1.1k tokens
Counted across 779 of the 1,178 authors here whose files we hold, read 2026-08-07
- Document a rollback plan before deploymentin 41 of 779, across 22 files
- Update the changelogin 21 of 779, across 19 files
- Run the test suitein 20 of 779
- Create an annotated git tagin 20 of 779
- Clean up feature flags after full rolloutin 18 of 779, across 10 files
- Verify deployment health after launchin 18 of 779, across 10 files
- Test both feature flag statesin 17 of 779, across 9 files
- Verify the working tree is cleanin 17 of 779
- Make database migrations backward-compatiblein 16 of 779, across 8 files
- Set up error monitoring before launchin 15 of 779, across 7 files
- Monitor metrics at each rollout stagein 14 of 779, across 5 files
- Create a GitHub releasein 14 of 779
Said here and by no other author read
- inventory production prompts and shelved ideas
- convert release note claims into testable hypotheses
- design resurrection tests from historical kill reasons
- rank the test plan within the stated budget
- state which items are cut from the budget
- fill verdict templates only from run results
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.