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5-osp-qa

OSP Phase 5: Multi-Aspect Q&A — configurable pairs per criterion (default 2)

Install / Use

npx skills add amirkiarafiei/open-scholar-peer --skill 5-osp-qa

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

69/100

Supported Platforms

Universal

Tags

Our assessment of 5-osp-qa

5-osp-qa scores 69/100 on our quality scale, 1090th of 1,185 Content & Media skills we index.

Its SKILL.md is 6.0 KB long, well organised into 10 sections and no code examples: a thorough specification that gives an agent plenty to work with.

It has no GitHub stars yet, so there is no community track record; judge it on its content.

Substance
29/30
Structure
13/20
Description
12/15
Adoption
0/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 22 days ago, so 5-osp-qa is actively maintained.
  • No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
  • Its trust signals score 80/100, with 2 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

5-osp-qa compared with similar skills

All 4 of these similar skills score higher than 5-osp-qa; compare them before choosing.

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5-osp-qa (this skill)by amirkiarafiei69022d agoSKILL.md
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Frequently asked questions

How do I install 5-osp-qa?
Run npx skills add amirkiarafiei/open-scholar-peer --skill 5-osp-qa. The install tabs above show the steps for each supported agent.
Which AI agents does 5-osp-qa work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is 5-osp-qa safe to use?
It declares no license and scores 80/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is 5-osp-qa still maintained?
The repository was last updated 22 days ago, so 5-osp-qa is actively maintained.

name: 5-osp-qa description: "OSP Phase 5: Multi-Aspect Q&A — configurable pairs per criterion (default 2)"

Tool capability: This tool does NOT support subagents. Use the self-reflection fallback: strict turn markers (=== Query Agent === ... === END === === Answer Generator === ...) within the main context window. This is a documented weaker substitute — see KNOWN_LIMITATIONS.md.

/5-osp-qa — Multi-Aspect Q&A Engine

For each criterion in session.json.qa_criteria[], generate N probing Q&A pairs (N = qa_pairs_per_criterion, default 2). The Query Agent runs in the main thread; the Answer Generator runs as a subagent (or self-reflects on the few tools that lack them).

Activation

Invoke the osp-query-agent skill (main thread). The Query Agent will spawn osp-answer-generator-agent per question.

Inputs — none of these is a gate

  • phases.summary.status, phases.literature.status, phases.historian.status and phases.baseline_scout.status. Each one that is missing removes a source of evidence, not the phase: no summary means you question the paper directly; no literature or narrative means novelty claims cannot be checked against prior work; no baseline scout means no missing-baseline questions. Run with what exists, name each gap in the artifact's Provenance, and let the answers say "could not be verified" rather than guessing.
  • qa_criteria[] in session.json. If it is empty, onboarding never ran — use the generic criteria from .cline/defaults/generic_review_guidelines.md and record that you did.

Record any skip before you start. The orchestrator is not in the loop when the user runs this command directly, so it falls to you: for every earlier phase still pending, set phases.<name>.status = "skipped" and phases.<name>.skip_reason to their reason, or "user ran /5-osp-qa first". A phase left pending reads as "not reached yet", and the final review cannot tell the difference.

Step 0 — Resource check and pair count (run BEFORE any Q&A work)

  1. Read session.json. Count qa_criteria[] items (call it C).

  2. Read qa_pairs_per_criterion from session.json (default 2 if absent).

  3. Print the resource estimate:

    ⚠️  Q&A Engine — resource estimate
       Criteria:  C
       Pairs/criterion: N  (currently set in session.json)
       Total subagent calls: C × N = <total>
       Estimated time: ~<total × 45s> at typical API latency
    
       Pair count guide:
         2  — quick scan, catches the most obvious issues         (default)
         5  — thorough coverage, good for most reviews
         10 — exhaustive, suitable for high-stakes decisions
    
  4. Ask the user: "How many Q&A pairs per criterion? Press Enter for [N] or type a number (2–10):"

  5. If the user enters a number, update session.json.qa_pairs_per_criterion to that value and use it. If the user presses Enter, use the existing value.

Mode selection

The banner at the top of this command says which mode your tool is in.

  • Subagent mode (default): the Query Agent delegates each question to the Answer Generator as a subagent with a fresh, minimal context bundle.
  • Prefer-subagent mode: try delegation first; if it is unavailable in your session, fall back to self-reflection and keep going rather than stopping the phase.
  • Self-reflection mode: the Query Agent uses strict turn markers (=== Query Agent === ... === END === === Answer Generator === ...) within the main context window.

Whichever you end up using, record it as Mode: in each file's ## Method section.

Opening block (print before step 1)

Render the opening block exactly as .cline/defaults/phase_block_template.md defines it — that file holds the rail, the rules and the widths, and it is the only place they are written down. This is phase 6 of 7 (qa); read the rail's state from session.json. Values:

  DOING    probe each criterion, and verify the answers
  READS    .brain/raw/ summary, narrative, baselines
  WRITES   .brain/raw/05_qa_<slug>.md   (one per criterion)
  COST     <C>x<N> subagent calls, ~45 s each

Steps

  1. Read all input artifacts listed in the frontmatter.
  2. Activate the osp-query-agent skill.
  3. For each criterion in qa_criteria[]:
    • Open or initialize .brain/raw/05_qa_<criterion_slug>.md from .cline/defaults/qa_pair_template.md.
    • Generate exactly qa_pairs_per_criterion Q&A pairs:
      • For each, the Query Agent formulates a probing question grounded in the structured summary, narrative, and missing baselines.
      • The Query Agent delegates to the Answer Generator (subagent or self-reflection per mode).
      • The Answer Generator returns (answer, citations, discrepancy_flag).
      • The pair is appended to the file.
    • Update phases.qa.criteria_progress[<slug>] = "completed".
  4. After all criteria are done:
    • phases.qa.status = "completed"
    • phases.qa.notes = "<C> criteria × <N> pairs each; <M> discrepancies flagged"
    • resume_from = "review"

Closing block (print when the phase ends)

Render the closing block from .cline/defaults/phase_block_template.md. Build the rail from session.json — ● only where status == "completed", ○ for pending and skipped. A phase the user skipped must not show as done. Drop BLOCKED and NOTE when there is nothing to put on them. Values:

  DONE     <N> pairs, <C> criteria, <M> discrepancies
           .brain/raw/05_qa_<slug>.md
  NEXT     /6-osp-review   write the review

Re-run behavior

Re-running overwrites 05_qa_<slug>.md for every criterion it covers, and these files cost the most of anything here — one subagent call per pair. Say what will be lost and wait for an answer before overwriting. To redo a single criterion, pass its slug as an argument; the rest are left alone.

Pitfalls

  • The Answer Generator must NOT see prior questions in subagent mode. Each invocation is stateless.
  • The Query Agent must NOT answer its own questions.
  • Do not generate fewer pairs than qa_pairs_per_criterion. The count must match exactly.

Related Skills

View on GitHub
GitHub Stars0
CategoryContent
Updated22d ago
Forks0

Trust signals

80/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

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