BO
96 souls, by quality score.
01 · № 03DD·36E8 · Research analyst
★ 17A terse, fact-only research persona modeled on the Salamanca brothers from Breaking Bad: two agents split web and internal sources, deliver a short findings-source-conclusion report, admit when nothing is found, and keep data within the team.
02 · № 62FB·8656 · Research analyst
★ 87Sets up a calm, direct research assistant that verifies facts with tools before answering, keeps answers concise but auditable, and separates confirmed results from inferences and screening signals. It refuses to present outputs as clinical decisions or scientific proof.
03 · № AD09·F8B7 · Research analyst
★ 744Sets up Memora as a persistent memory service that stores only what callers provide, returns structured results with source ids, and exposes uncertainty through warnings and status rather than prose. It favors deterministic aggregation, protects document roots from accidental destructive edits, and does not vouch for the truth of stored content.
04 · № 68A7·A2EA · Research analyst
★ 281Sets up a self-hosted web-research agent that searches and extracts public web sources, reports findings with citations, and defaults to assisting with legitimate lookups while refusing clearly harmful targeting. Output is concise and technical.
05 · № 21B2·CB49 · Research analyst
★ 82Sets up a precise, formal research agent for mathematical physics that favors derivations, LaTeX sources, and Srednicki's mostly-plus metric, and stays within its domain. It is concise and open about limitations.
06 · № D095·85E9 · Research analyst
★ 25Sets up Kit as a curious, methodical scout who maps unfamiliar codebases before others code, documents for strangers, reports only what it can verify, and hands off cleanly to developer and QA roles.
07 · № 5856·28EE · Research analyst
★ 940A methodical, low-noise code analysis agent that extracts UX patterns from frontend repos, reports only high-confidence findings with evidence, and advises without blocking PRs. It maintains a shared UX principles document and creates tickets for actionable issues.
08 · № 5319·99F6 · Research analyst
★ 6Sets up a sharp, cynical forensic systems analyst who reasons in causal chains, cites sources for every claim, delivers one finding at a time and refuses to accept surface fixes or "we didn't know" excuses.
09 · № F652·20D6 · Research analyst
★ 14A calm, methodical research engineer persona that values verified steps, written records and honest uncertainty. It separates confirmed facts from inferences and open risks, and defaults to Chinese in its workspace.
10 · № E1D3·37CF · Research analyst
★ 28Sets up GeoClaw as a structured, transparent geospatial workflow agent that prefers registered tools, treats input data as read-only, checks CRS and scale, and documents assumptions and limitations. It stays collaborative and avoids replacing the user's judgement.
11 · № A980·61FB · Research analyst
★ 24Sets up Alhazen, a methodical scientific knowledge notebook that traces every claim to evidence, flags uncertainty, and stores provenance in a TypeDB graph. It also specializes the agent in job search tracking and delegates pipeline work to a JobCoach sub-agent.
12 · № DE6D·CAFB · Research analyst
★ 836Sets up a terse, evidence-led working style that replies in concise Chinese, leads with conclusions, avoids overclaiming, and makes minimal, careful changes. Persona settings are explicitly subordinate to approval gates and destructive-action safeguards.
13 · № 3CDE·7CA7 · Research analyst
★ 1Sets up a Korean-speaking requirements partner that asks one decision question per turn, recommends safe defaults with their impact, scores clarity and ambiguity, and avoids implementing during the dialogue stage.
14 · № B109·7554 · Research analyst
★ 315Sets up Lavern as a careful legal-document assistant that explains complex legal concepts in plain language first, cites specific text, admits uncertainty, and stays conservative on risk while formal in deliverables. It is written for CLI or Claw mode with a browser profile taking priority when available.
15 · № A89B·3225 · Research analyst
★ 3.0kSets up an agent that checks factual claims against authoritative regulatory sources, verifies rule numbers, effective dates and citations, and explicitly flags anything it cannot verify rather than assuming it is correct.
16 · № E86C·213A · Research analyst
★ 11Sets up a cautious security analyst that scores emails and URLs for phishing indicators using structure-only analysis, flags uncertain cases for human review, explains its red flags to users, and produces periodic phishing trend reports.
17 · № 9E62·7F98 · Research analyst
seen in 2 placesSets up a calm, evidence-based retrospective agent that runs only after a task ends, reviews full logs against the blueprint, gives constructive criticism of work rather than of agents, and turns lessons into updates to AGENTS.md and MEMORY.md.
18 · № 145C·2176 · Research analyst
★ 80Sets up an analytical, engineering-minded voice that breaks problems into structure, weighs incentives, costs and execution conditions, and explains complex issues clearly. It allows light irony and judgment but avoids performative answers.
19 · № 4EE6·D235 · Research analyst
★ 36A data-driven monitoring persona for Toutiao that searches hot topics and viral articles and produces stable, structured daily reports for downstream tools. It never publishes or operates accounts, and it answers concisely with sources and time ranges noted.
20 · № 226D·1D08 · Research analyst
★ 70Sets up an analyst that verifies claims against independent sources, flags conflicts between administrative data and frontline accounts, and insists on specific clinical and regulatory metrics in patient safety assessments.
21 · № B3D7·02AB · Research analyst
★ 4Sets up a terse researcher persona that cites a source for every claim, refuses to paraphrase speculatively or round numbers, flags uncertainty explicitly, and prefers short outlines.
22 · № 1392·D1EB · Research analyst
★ 4Sets up a worldbuilding agent that treats canon literally, quotes sources rather than paraphrasing, and refuses to let unstated details slip in. The voice is terse and exacting.
23 · № 0923·7B63 · Research analyst
★ 3Sets up Mélisande, a research persona that values clarity over volume, extracts what matters from complex evidence, reconciles contradictions honestly, and refuses padded summaries or buried insights.
24 · № 4595·6694 · Research analyst
★ 1Sets up a candid product partner that ties features to user outcomes, separates evidence from judgment, flags unknowns, and recommends narrower scope or more discovery when evidence is thin.
25 · № 6CA0·B293 · Research analyst
★ 1Sets up a careful, systematic research partner that cites sources, asks scoping questions early, shows its methodology, and explicitly quantifies uncertainty. Explains findings in plain language without condescension.
26 · № F4FA·944F · Research analyst
★ 16A terse, systematic paper-search subagent that picks 3-5 academic sources, follows a skill manual for API calls, deduplicates results and writes candidates and logs to files without fabricating papers. It sets up a librarian-like working style with fallback rules when fetches fail.
27 · № D5DE·4860 · Research analyst
★ 22Sets up a senior designer who favors reliability, proven patterns and low operational risk. It asks for explicit tradeoffs, avoidance of fragile dependencies, and secure, testable, rollback-friendly designs.
28 · № A1EE·1DD6 · Research analyst
Sets up a coordinated investment research desk of specialized agents that gather tool-backed evidence before forming views, state uncertainty explicitly, and leave the final investment decision to the user. The voice is calm, direct and specific with no hype.
29 · № 9D2A·3D3E · Research analyst
Sets up a direct, data-first market research analyst for a small bootstrapped Quebec ag-tech team. The assistant is honestly skeptical, flags French-market translation needs, and ends every analysis with concrete next steps for the founder.
30 · № CBAA·46BE · Research analyst
Sets up a skeptical, precise agent that separates root causes from symptoms, triggers and controls, marks each claim as observed, inferred or uncertain, and keeps analysis evidence-based across technical, process and organizational layers. It asks for concise, structured output written for downstream agents.