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baladithyab
GitHub 제작자 프로필

baladithyab

3개 GitHub 저장소에서 수집된 21개 skills를 저장소 단위로 보여줍니다.

수집된 skills
21
저장소
3
업데이트
2026-06-16
저장소 탐색

저장소와 대표 skills

hyperresearch-1-decompose
시장조사 분석가·마케팅 전문가

Step 1 of the hyperresearch V8 pipeline. Decomposes the canonical research query into atomic items, classifies pipeline_tier and response_format, and produces the coverage matrix that downstream steps depend on. The required_section_headings field this step produces is the single highest-leverage input for instruction-following scores. Invoked via Skill tool from the entry skill (hyperresearch).

2026-06-16
hyperresearch-10-triple-draft
시장조사 분석가·마케팅 전문가

Step 10 of the hyperresearch V8 pipeline. Orchestrator pre-curates 20-50 angle-specific source IDs per draft, then spawns 3 hyperresearch-draft- orchestrator subagents in parallel — each reads its curated list (no vault surveys, no source-fetching) and writes one angle-specific draft. This step ENDS when all 3 drafts are written and validated. Step 11 (synthesizer) handles the synthesis-write that produces the final report. For light tier: writes a single draft directly to final_report.md and skips ahead to step 15 (polish). Invoked via Skill tool.

2026-06-16
hyperresearch-11-synthesize
시장조사 분석가·마케팅 전문가

Step 11 of the hyperresearch V8 pipeline. Reads the 3 angle-specific drafts from step 10, spot-checks factual conflicts, writes a synthesis plan + outline, then spawns ONE hyperresearch-synthesizer subagent (Read+Write tool-locked) that writes the final report in TWO passes — pass 1 rough integrated draft, pass 2 voice/redundancy/length cleanup. Skipped for light tier (which writes a single draft directly in step 10). Invoked via Skill tool from the entry skill (full tier).

2026-06-16
hyperresearch-12-critics
시장조사 분석가·마케팅 전문가

Step 12 of the hyperresearch V8 pipeline. Spawns 4 adversarial critics in parallel against the synthesized final report from step 11. Each critic produces an independent findings JSON that the patcher (step 14) consumes. Critics never modify the draft directly. Invoked via Skill tool from the entry skill (full tier only).

2026-06-16
hyperresearch-13-gap-fetch
시장조사 분석가·마케팅 전문가

Step 13 of the hyperresearch V8 pipeline. Conditional fetcher wave to fill vault gaps that critics identified. If a critic says "the draft ignored topic X" and the vault has zero sources on X, the patcher has nothing to cite. This step fetches the missing sources BEFORE patching so the patcher has ammunition. Capped at 5 gaps. Invoked via Skill tool from the entry skill (full tier).

2026-06-16
hyperresearch-14-patcher
소프트웨어 개발자

Step 14 of the hyperresearch V8 pipeline. Spawns the hyperresearch-patcher subagent (TOOL-LOCKED to Read + Edit) to apply critic findings as surgical Edit hunks against the synthesized final report. Zero regeneration. Pre-stubs the patch log because Edit cannot create files. Handles orchestrator-escalated structural restructures inline. Invoked via Skill tool from the entry skill (full tier).

2026-06-16
hyperresearch-15-polish
소프트웨어 개발자

Step 15 (final) of the hyperresearch V8 pipeline. Spawns the hyperresearch-polish-auditor subagent (TOOL-LOCKED to Read + Edit) for the final hygiene + readability pass. Strips pipeline-reference leaks, YAML frontmatter, scaffold sections, filler phrases, run-on sentences. Escalates structural mismatches rather than fabricating content. Invoked via Skill tool from the entry skill. Followed by step 16 (readability audit) which is the actual final step before ship.

2026-06-16
hyperresearch-16-readability-audit
소프트웨어 개발자

Step 16 (final) of the hyperresearch V8 pipeline. Spawns the hyperresearch-readability-recommender subagent (Read+Write tool-locked, Opus) to audit the polished final report and write JSON recommendations for paragraph merges, breaks, list/table conversions, bold injection, sentence splits, and HR removal. The orchestrator reads the recommendations and SELECTIVELY applies them via direct Edit calls (the recommender does NOT modify the report itself). Logs orchestrator decisions to a separate file. Runs for ALL tiers. Invoked via Skill tool from the entry skill.

2026-06-16
이 저장소에서 수집된 skills 16개 중 상위 8개를 표시합니다.
surrealql-reference
소프트웨어 개발자

Use this skill when you need to write SurrealQL queries or schema definitions. Triggers on: "SurrealQL", "SurrealDB query", "surql", "DEFINE", "SELECT FROM", "CREATE TABLE", "RELATE", "full-text search", "vector search", "HNSW", "graph traversal", "computed field", "memory strength decay", "knowledge graph", "edge queries", "record link", "UPSERT", "BM25", "search operator", "@1@", "SPLIT", "FETCH". Use this skill to understand exact SurrealQL syntax for the surrealdb-memory plugin.

2026-02-26
surrealql
데이터베이스 아키텍트

This skill should be used when writing SurrealQL queries for SurrealDB 3.0, modifying the engram schema, or debugging SurrealQL errors. Triggers on: "SurrealQL", "surql", "SurrealDB query", "schema change", "DEFINE TABLE", "DEFINE FIELD", "DEFINE INDEX", "UPSERT", "RELATE", or any SurrealDB DDL.

2026-02-26
memory-admin
소프트웨어 개발자

This skill should be used when the user asks to "manage memory", "consolidate memories", "promote memories", "archive old memories", "check memory health", "prune knowledge graph", "switch deployment mode", "export memory", or needs guidance on memory lifecycle management. Covers: consolidation pipeline, promotion criteria, archival, knowledge graph maintenance, deployment mode switching, memory diagnostics, and troubleshooting.

2026-02-25
memory-query
소프트웨어 개발자

This skill should be used when the user asks to "search memories", "find in memory", "what do I remember about X", "recall past decisions", "check memory for X", or needs guidance on constructing memory queries. Covers: MCP tool usage patterns, memory type selection (episodic/semantic/procedural/working), scope selection (session/project/user), importance scoring, and retrieval strategies (BM25, graph, hybrid).

2026-02-23
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