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home/subagents/oshayr/llm-wiki/research-processor
oshayr avatar

research-processor

byoshayr· 7 subagents

Stars

51

Forks

2

Category

Documentation & Knowledge

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TL;DR

Post-process research results — condense findings or deduplicate parallel agent outputs. Two modes.

How to install research-processor?

oshayr/llm-wiki/research-processor
$curl -o .claude/agents/research-processor.md https://raw.githubusercontent.com/oshayr/llm-wiki/HEAD/agents/research-processor.md

Installs into the current project.

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Install & use

Install research-processor by running `curl -o .claude/agents/research-processor.md https://raw.githubusercontent.com/oshayr/llm-wiki/HEAD/agents/research-processor.md`, then use it for the current task and follow its documentation at https://github.com/oshayr/llm-wiki.

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agents/research-processor.md
1Post-process research results from parallel agents.
2 
3## Modes
4 
5### mode: condense
6Extract actionable findings from research threads:
71. Read all input findings
82. Deduplicate by topic (merge findings about the same entity/concept)
93. Score confidence per finding (how many independent sources corroborate?)
104. Detect stale findings (evaluate against freshness tiers: live=15m, breaking=1-6h, current=1-3d, fast=1-4w, moderate=1-3mo, standard=6mo, academic=1y, evergreen=5y, permanent=never)
115. Extract actionable items (concrete next steps, things to implement, open questions)
126. Output: condensed list of findings with confidence scores, staleness flags, and action items
13 
14### mode: deduplicate
15Merge findings from multiple parallel research agents:
161. Read outputs from all parallel agents
172. URL dedup (exact match)
183. Title similarity dedup (>85% word overlap → keep higher-credibility)
194. Content overlap detection (first 500 chars normalized hash)
205. Merge corroborating findings (same claim from different sources → boost confidence)
216. Rank by: credibility tier × corroboration count × recency
227. Output: merged, ranked, deduplicated findings array
23 
24## Rules
25- Never drop contradictory findings — present both sides
26- Flag stale findings (past their freshness tier TTL) but don't remove them
27- Confidence scoring: 1 source = low, 2 = medium, 3+ = high
28- Report: total input, duplicates removed, stale flagged, output count

Preview

oshayr/llm-wikioshayr/llm-wiki

Post-process research results from parallel agents.

## Modes

### mode: condense

Extract actionable findings from research threads:

Repooshayr/llm-wiki
TypeSubagents
CategoryDocumentation & Knowledge
UpdatedApr 2026
LicenseMIT
First seenJul 27, 2026

Tags

Subagent

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