agentsclimarketplace

Sprint eval

Skill anupam-io/sprint-skills/skills/sprint-eval

Agent skills that turn a one-line goal into a dependency-ordered sprint of GitHub issues, then run them one at a time — review-each (HITL) or fully unattended (AFK). No cluster, no Linear: just gh, claude, and your repo.

Install
npx -y skills add anupam-io/sprint-skills --skill sprint-eval

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 0 stars0 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.

What its author says it does

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Rate a sprint plan by convening a panel of 3 local expert agents (engineering program management, operations-research scheduling, agentic task planning), each scoring the same 3 fixed criteria 1-10, then synthesizing a score table, consensus risks, and concrete fixes. Use when the user wants a sprint plan rated/evaluated/stress-tested, asks "how good is this sprint plan", or hands over a sprint doc asking for a quality verdict. Input is a sprint plan in any format (HTML, markdown, Slack dump, Linear export).

SKILL.md

4.0 KB, as published. Nobody here has run it

Sprint Eval

Panel-based sprint plan rating. Three independent expert agents read the SAME plan and score the SAME criteria, so scores are comparable and agreement is signal: anything all three flag independently is almost certainly real.

Input

A sprint plan: a file path or pasted text. If it's a file, pass the path to the agents and let each read it themselves (independent reads, no shared summary — don't pre-digest the plan for them, that would correlate their errors).

Fixed criteria (same for every rater)

  1. Dependency & sequencing health — critical path soundness, blocker surfacing/ordering, cross-person handoffs.
  2. Capacity realism & load balance — per-person allocation vs the sprint horizon, onboarding load, P0 distribution.
  3. Goal alignment & scope discipline — must-ship items map to stated targets; cancel/backlog/carry-over hygiene; clarity.

The panel

Spawn all 3 in ONE message (parallel Agent calls, general-purpose). Each gets a distinct lens so they catch different failure modes:

RaterPersonaLens emphasis
EPMVeteran engineering program manager, 15y of 2-week cycleshandoffs, single points of failure, priority inversion
OROperations-research scheduling specialist (CPM/PERT, resource-constrained scheduling)chain depth vs horizon, slack, utilization vs variance buffer, negative-slack chains
AgenticExpert in agentic task planning — crisp specs, explicit interfaces, verifiable done-conditionshidden couplings, unspecified API contracts, vague acceptance criteria, TBD items

Every prompt must include, verbatim in spirit:

  • the 3 fixed criteria, phrased through that rater's lens;
  • "Return raw data only (your final message is consumed by a program, not a human): for each criterion give score: N/10 plus 2-3 sentences of justification grounded in specifics from the plan, then one line top risk: with the single biggest thing you'd flag.";
  • "Be a tough but fair grader; don't inflate."

Domain swap: if the sprint is clearly outside software (e.g. content, ops), swap the EPM persona for the matching domain planner; keep OR and Agentic — they're domain-agnostic.

Synthesis (your final answer)

Lead with the verdict: overall average to one decimal, e.g. "≈ 4.7/10".

  1. Score table — criterion rows × rater columns + per-criterion average.
  2. Unanimous findings first — anything 2-3 raters flagged independently, named as such ("all three named X"). The intersection is the headline, not your own opinion.
  3. Lens-unique catches — findings only one expert saw (typically the Agentic rater's interface/spec gaps), attributed to the lens.
  4. What scored well — 2-4 genuine strengths; a panel that only criticizes is uncalibrated.
  5. Top 2 fixes — concrete, smallest-change recommendations ("shed ~4 of X's items to Y", "ticket the 7 missing integrations or rewrite the target"), not generic advice.

Do not average away disagreement: if raters split by ≥3 points on a criterion, say why (usually the OR rater counting days where others pattern-matched).

Sharp edges

  • Scores come from the agents, never from you; if an agent fails or returns no scores, rerun it rather than filling in numbers.
  • Keep raters blind to each other — no sharing of outputs between them, no "rater 2 said...".
  • Ground every claim in the plan's specifics (names, ticket ids, counts). A finding that can't cite the plan gets dropped from the synthesis.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.