idea-evaluator

Idea Evaluator

Overview

This skill evaluates a preliminary research idea from the combined perspective of a top-venue reviewer and an experienced advisor. It scores the idea against five improvement dimensions from the idea-generation guide (Higher, Faster, Stronger, Cheaper, Broader), matches the idea's lifecycle against the user's actual capability and available hours per week, probes whether the idea has paradigm-shift potential, flags fatal flaws, and returns one of three verdicts: Strong Accept, Accept with Revisions, or Reject and Pivot.

The goal is to kill weak ideas before the student invests months, and to shape promising-but-underdeveloped ideas into stronger forms before writing begins.

When to use this skill

• The user has a draft idea and asks whether it is worth pursuing.
• The user asks for novelty check, feasibility assessment, or scoring.
• Before the user commits to a paper scope or starts implementation.
• The user is comparing two or three candidate ideas and needs a structured trade-off.
• The user suspects scope creep and wants an external check.
• The user mentions 'evaluate this idea', 'score this idea', 'assess feasibility', or 'is this a good research direction'.

When NOT to use this skill

• The user has already implemented the idea and is writing the paper. Use intro-drafter, tech-paper-template, or benchmark-paper-template (separate plugin) instead.
• The user explicitly wants brainstorming of new ideas from scratch. Use plain conversation; see handbook 2.3 for a disruptive-innovation playbook.
• The user asks for review of an existing manuscript. Use pre-submission-reviewer.
• The user asks to evaluate a benchmark contribution specifically. Use benchmark-paper-template (separate plugin) in targeted mode.

Core procedure

Step 1: First impression and paper-type positioning

Read the user's idea description. In one paragraph, state whether the idea reads as Novel Problem, Novel Method, or New Setting. Is the story compelling in one sentence? If you cannot write that sentence, the idea itself is probably not yet clear enough for evaluation; ask the user to restate.

While restating, classify the research paradigm by method, not by department name: experiments, benchmarks, ablations, or model architectures mean STEM (continue with the five dimensions and fatal flaws below); text analysis, archives, or conceptual argument mean humanities; surveys, interviews, statistics, or fieldwork mean empirical social science; regressions, IV, DID, RDD, or panel data mean finance or economics; statutes, cases, or doctrine mean law.

See: references/domain-evaluation-frameworks.md for the substitute five-dimension frameworks and fatal-flaw substitutions used by the non-STEM paradigms. When the paradigm is unclear, ask one question: "is the core method experiments, surveys, text analysis, or theoretical derivation?"

Step 2: Fatal-flaws audit (early gate)

See: references/fatal-flaws.md for the ten canonical fatal flaws, each with a detection rule and a defense strategy.

Run the fatal-flaws audit before the scoring steps rather than after them. Identify at most two fatal flaws. For each, state the flaw, cite the detection rule, and recommend a concrete defense.

Ground the novelty flaw (F1) in real retrieval whenever the environment has a literature-search capability (a scholarly search tool, web search over scholarly indexes, or shell access to public APIs). Extract two or three keyword groups from the idea (core method plus domain; mechanism plus task; technique plus benchmark), search, and name the three to five closest published works with title, authors, and year. For each, state which axis actually differs: the object acted on, the mechanism, the input granularity, or the problem setting. A similar title alone never establishes duplication; duplication requires failing to find even one differing axis. Retrieval results support metadata-level judgments only (who did what, where); never quote numbers or method details from search snippets. And "not found" does not prove novelty: report it as "no directly overlapping work retrieved under these keywords". With no retrieval capability, label the novelty judgment "unverified; literature check required".

A data-refuted core mechanism is an automatic CRITICAL. If the user's own reported data or attachments already show the core mechanism matched or beaten by a baseline or simple control, lock the verdict to Reject and Pivot; write no defense and invent no optimistic threshold. See: references/fatal-flaws.md, the data-refuted section, for the exact boundary between "refuted by data" and "merely untested".

Short-circuit rule. If any fatal flaw is tagged CRITICAL in the severity taxonomy (single-handedly causes rejection, unfixable within the lifecycle), stop here and emit the verdict directly:

• Verdict: Reject and Pivot.
• Output sections 1 (First impression), 2 (Fatal flaws with the CRITICAL flaw), and 7 (Verdict with the flaw-driven rationale) only.
• Do not run the five-dimension scoring, paradigm-shift probe, feasibility check, or integrity gate. Those would be decoration on a rejection.

If no CRITICAL flaw is found, continue to Step 3.

Step 3: Lifecycle and capability matching

See: references/lifecycle-capability-matching.md for the six-category lifecycle matrix, capability self-assessment rubric, and mismatch recovery strategies.

Map the idea onto one of six categories (Application, Foundational Theory, Cross-Disciplinary, Frontier Exploration, Data-Intensive, Innovative Technique). Match against the user's declared capability (effective hours per week, skill depth, theoretical versus applied strength). Output a mismatch flag if lifecycle is shorter than the user's realistic execution window.

Step 4: Five-dimension scoring

See: references/five-dimensions.md for each dimension's entry strategies, scoring rubric, and worked examples.

Score the idea on each of:

• Higher: effectiveness and accuracy gains.
• Faster: efficiency and cost reduction.
• Stronger: robustness, noise tolerance, generalisation.
• Cheaper: data, annotation, or solution cost reduction.
• Broader: cross-domain transplantation or unification.

Score each 1-10 with explicit evidence from the user's stated contribution. Identify the two or three dimensions where the idea has the highest ceiling and recommend emphasising those in the paper.

Scoring discipline: start every dimension at 5 and justify movement. Two kinds of grounds move a score up, and both count: measured results the user reported (quote them), or a mechanism argument that holds up (label the score "mechanism-based, not yet confirmed by data"). A solid, untested mechanism can reach 8 or 9 with that label plus a named validation experiment; do not systematically cap untested ideas. A dimension with neither data nor mechanism stays at 5 with "no grounds given". Watch attribution: when an impressive gain plausibly comes from a peripheral factor (routing, post-processing, a stronger base model, favorable samples), cap that dimension until an ablation isolates the core mechanism. The scoring reference's final two sections cover both rules in detail.

For non-STEM paradigms, score the substitute dimensions from references/domain-evaluation-frameworks.md instead, under the same discipline.

Step 5: Paradigm-shift probe

See: references/paradigm-shift-probe.md for the four probing principles (First Principles, Elephant in the Room, Technology Cycle, Hamming's Rule) and the cross-reference to handbook section 2.3 when deeper disruptive-innovation exploration is needed.

Test the idea against four questions:

1. Does it challenge a hidden assumption the field takes for granted?
2. Does it address an elephant-in-the-room problem everyone sees but nobody wants to touch?
3. Does it ride a technology-cycle shift (for example, LLMs making a previously impractical approach now feasible)?
4. If this problem solved itself, would the field change meaningfully? (Hamming's Rule)

Two or more yes answers means the idea has disruptive potential. Note that, and recommend reading handbook 2.3 to deepen the thinking on disruptive-innovation dimensions.

Step 6: Feasibility check

Against the user's stated resources (hardware, data access, team size, engineering skills, timeline), assess:

• Compute risk: does the experiment fit on stated hardware?
• Data risk: is the required data accessible, or does it need expensive annotation or private sources?
• Engineering risk: does the implementation match the user's skill stack?
• Timeline risk: does the estimated end-to-end duration (coding, experiments, writing, revision) fit within the idea's lifecycle?

If any risk is high, flag it explicitly with a suggested mitigation.

Step 7: Integrity gate

Before emitting the verdict, run the checks in the Integrity gate section below.

Step 8: Final verdict

Issue one of three verdicts:

• Strong Accept: execute now. Two or more dimensions at 8+, no fatal flaws, capability match green, lifecycle fit.
• Accept with Revisions: pivot the scope per recommendations before starting. Some dimensions weak, fixable flaws, or lifecycle mismatch that can be shortened.
• Reject and Pivot: do not pursue this version. Dominated by a prior benchmark or method, unfixable capability mismatch, or more than one fatal flaw.

When the high scores are mechanism-based rather than data-based, qualify the verdict as "worth pursuing, pending the validation experiment", and name that experiment in the top-three actions.

Emit the evaluation in the Output format below.

Integrity gate

Each bullet is tagged with an enforceability class. [inspection] means the LLM can verify the bullet from the produced output alone. [attestation] means the LLM states it has done the check, but the user remains responsible for verification. [user-attest] means the bullet is a user-side rule the skill cannot confirm.

Before returning the verdict:

1. [inspection] Every dimension score cites specific evidence from the user's stated contribution; no score is "gut feeling".
2. [inspection] Feasibility claims reference the user's stated resources, not generic assumptions.
3. [inspection] Novelty claims either cite specific prior work or are labelled "unverified; literature check required".
4. [inspection] Fatal flaws are specific and actionable; "this might not work" is not a flaw statement.
5. [inspection] Verdict is consistent with scoring: Strong Accept requires at least two dimensions at 8+ and zero CRITICAL flaws.
6. [inspection] Paradigm-shift claim cites which probing question was answered positively.
7. [attestation] Lifecycle prediction is reasoned from the field's recent pace; the user should sanity-check against their own knowledge of the subfield before acting on it.

If any [inspection] check fails, downgrade the verdict and mark the corresponding output section as "needs user attention". For [attestation] bullets, the skill states the check was run and the user confirms the result.

Run the gate silently. Do not print a per-gate pass or fail report; a failure surfaces as a concrete finding inside the affected output section, and the delivered evaluation stays free of internal checking rituals.

Output format

1. First impression

• Paper type:
• One-sentence story: <...>

2. Fatal-flaws audit (early gate)

If any CRITICAL flaw is present, skip sections 3-6 and go to section 7 with verdict Reject and Pivot.

3. Lifecycle and capability match

4. Five-dimension radar

5. Paradigm-shift probe

Disruptive potential: <none, possible, strong>.

6. Feasibility

7. Verdict

(mechanism-based high scores: append "worth pursuing, pending the validation experiment")

Top three actions to take first:

1. ...
2. ...
3. ...