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@c5c1b45

Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 8 modes: full research, quick brief, paper review, lit-review, fact-check, three-way literature scan, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, WHY HOW WHAT papers, 3W literature scan, guide my research, help me think through, 研究, 深度研究, 文獻回顧, 文獻探討, 系統性回顧, 後設分析, 事實查核, 三段式文獻掃描, 引導我的研究, 幫我釐清, 幫我想想, 我不確定要研究什麼, 研究方向, 研究主題, 심층 연구, 문헌 조사, 체계적 문헌고찰, 메타분석, 사실 확인, 연구 방향을 잡아줘, 연구 주제 정하는 것을 도와줘, revisión de literatura, metaanálisis

Use this Skill: https://skilld.dev/gh/imbad0202/academic-research-skills/deep-research

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templatesevidence_assessment_template.md

≈1.6k tokens on demand. Your agent reads this file only when SKILL.md points to it.

Evidence Assessment Template

Purpose

Per-source quality assessment card. Used by the source_verification_agent to systematically evaluate each source entering the research pipeline.

Assessment Card

## Evidence Assessment Card

### Source Identification
- **Citation (APA 7.0)**: [full reference]
- **DOI/URL**: [link]
- **Type**: [journal article / book / report / web / conference paper / thesis / other]
- **Access Date**: [when verified]

---

### Quality Assessment

#### 1. Evidence Level
**Level**: [I / II / III / IV / V / VI / VII]
**Justification**: [why this level]

#### 2. Publication Venue
- **Journal/Publisher**: [name]
- **Indexed in**: [Scopus / WoS / PubMed / DOAJ / other / none]
- **Impact Factor/CiteScore**: [value or N/A]
- **COPE member**: [Yes / No / Unknown]
- **Predatory indicators**: [None / Flags: list]

**Venue Grade**: [Excellent / Good / Adequate / Questionable / Unacceptable]

#### 3. Author Credibility
- **Author(s)**: [names]
- **Affiliation(s)**: [institutions]
- **ORCID**: [if available]
- **Track record**: [publication history in field]
- **Expertise match**: [relevant to topic? Yes/Partial/No]

**Author Grade**: [Excellent / Good / Adequate / Unknown / Questionable]

#### 4. Methodological Quality
- **Design**: [description]
- **Sample**: [size, selection, representativeness]
- **Analysis**: [appropriate for design?]
- **Limitations acknowledged**: [Yes / Partially / No, naming the sections checked / not assessed (read scope: <scope>)]
- **Replicable**: [Yes / Partially / No]
- **Method weaknesses**: [per the Method weaknesses rules below the card]

**Method Grade**: [Excellent / Good / Adequate / Weak / Flawed / Not assessed (read scope: <scope>)]

#### 5. Currency
- **Publication year**: [YYYY]
- **Data collection period**: [if stated]
- **Field velocity**: [Rapid / Moderate / Slow / Foundational]
- **Still current**: [Yes / Conditionally / No]

**Currency Grade**: [Current / Acceptable / Dated / Outdated / Foundational]

#### 6. Conflict of Interest
- **Declared COI**: [None / Listed: details]
- **Funding source**: [source or Not stated]
- **Potential undeclared COI**: [None detected / Possible: details]

**COI Grade**: [Clean / Minor / Moderate / Significant / Critical]

---

### Overall Assessment

| Dimension | Grade |
|-----------|-------|
| Evidence Level | [I-VII] |
| Venue | [Excellent-Unacceptable] |
| Author | [Excellent-Questionable] |
| Method | [Excellent-Flawed] |
| Currency | [Current-Outdated] |
| COI | [Clean-Critical] |
| **Overall** | **[A / B / C / D / F]** |

### Recommendation
- [ ] **Use as primary evidence** (Grade A-B)
- [ ] **Use as supporting evidence** (Grade B-C)
- [ ] **Use with explicit caveats** (Grade C-D)
- [ ] **Do not use** (Grade D-F) — Reason: [specific reason]

### Notes
[Any additional observations, caveats, or context]

Method weaknesses rules (§4)

<!-- method-weaknesses:begin -->

Method weaknesses (per source, #916). Information only. Nothing here blocks, gates, scores, or asks the scholar a question.

  1. Named design and failure condition. Name the specific design, measure, sample, or analysis choice, and the condition under which it would distort the result. "Small sample" alone is not enough; "n = 24 from one site, so the site effect cannot be separated from the treatment" is.
  2. Provenance label on every item. Mark each item author-acknowledged or reader-inferred. An author-acknowledged item carries a locator in one of the v3.7.3 anchor kinds (quote, page, section, paragraph). A reader-inferred item is an untested inference and says so.
  3. Bounded absence claims. A statement that the authors do not address X names the sections that were checked (the #548 search-bounded pattern). If those sections cannot be named, do not make the absence claim.
  4. Fixed aspect checklist. Use the source's paper-type table in academic-paper-reviewer/references/review_criteria_framework.md §2 (empirical, theoretical, review / meta-analysis, case study, policy). Mark each criterion in that table checked: found, checked: none found, or not checked. Stop at the end of the table; do not keep adding items until the list feels complete.
  5. No method-level weakness without the text. When only the abstract or table of contents is available, or the recorded read scope (/ars-mark-read --scope) is abstract_only, toc_only, or unknown, write not assessed (read scope: <scope>) and no inferred weaknesses. For sections, stay within the declared sections.

Do not turn a weakness into an improvement suggestion or research direction; that step stays with the scholar. Keep the entry short:

- **Method weaknesses** (<paper type>; read: <what was read>)
  - checked: found: <criterion>, ... | checked: none found: <criterion>, ... | not checked: <criterion>, ...
  - <design choice>; distorts the result when <condition>. [author-acknowledged, <anchor kind>: <locator>] or [reader-inferred]

or, when rule 5 applies, - **Method weaknesses**: not assessed (read scope: <scope>).

<!-- method-weaknesses:end -->

Batch Assessment Summary

## Source Verification Summary

**Date**: [YYYY-MM-DD]
**Sources assessed**: [N]
**Assessor**: source_verification_agent

### Grade Distribution
| Grade | Count | % |
|-------|-------|---|
| A (Excellent) | X | X% |
| B (Good) | X | X% |
| C (Adequate) | X | X% |
| D (Weak) | X | X% |
| F (Unacceptable) | X | X% |

### Flagged Sources
| Source | Issue | Severity | Recommendation |
|--------|-------|----------|---------------|
| [ref] | [issue] | [High/Medium/Low] | [Include with caveat / Exclude] |

### Predatory Journal Alerts
[List any flagged journals]

### Overall Source Base Quality
**Assessment**: [Strong / Adequate / Mixed / Weak]
**Recommendation**: [Proceed / Supplement / Major revision of source base needed]

Usage Notes

  • Complete one card per source for full verification
  • Batch summary should be produced after all cards are complete
  • Minimum spot-check: 20% of sources get full card assessment
  • All Grade D/F sources require documented justification
  • Any predatory journal flag requires full verification

Source: SKILL.md on GitHub

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  • Gen Agent Trust Hub1d

    The deep-research skill is a highly sophisticated research orchestration system that includes robust internal security instructions to prevent prompt injection from untrusted data. It leverages well-known scholarly APIs for data verification and uses local scripts for deterministic validation of research artifacts.

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    Score: 93/100 · 2 sections analyzed

Signed by skilld at c5c1b45. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 33 minutes ago.

Activeupdated 2 days ago
Other metadata
metadata
{
  "version": "2.12.1",
  "last_updated": "2026-08-15",
  "status": "active",
  "data_access_level": "raw",
  "task_type": "open-ended",
  "related_skills": [
    "academic-paper",
    "academic-pipeline"
  ]
}

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