GBrain is a memory and retrieval layer for AI agents that searches, connects, and synthesizes information from stored sources. It is used to give coding agents and autonomous agents access to knowledge beyond their current code, including shared company information with access controls. The catalogue add-ons help agents operate GBrain and connect it to agent workflows.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/garrytan/gbrainnpx agentmods add skills/garrytan/gbrain/concept-synthesisWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/garrytan/gbrain/concept-synthesis)<a href="https://agentmods.dev/skills/garrytan/gbrain/concept-synthesis"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/concept-synthesis.svg" alt="Measured on agentmods" height="20"></a>- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Output Handling · line 420 Output size or generation rate is not bounded. Unbounded output enables denial-of-service through resource exhaustion, log flooding, or context-window stuffing.Fix: Set explicit limits on output length, generation count, and rate. Use max_tokens and truncation to prevent unbounded output.
- medium Agent Snooping · line 495 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 496 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 497 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00090 | $0.05218 |
| Opus 5 | $0.00045 | $0.02609 |
| Sonnet 5 | $0.00018 | $0.01044 |
| Haiku 4.5 | $0.00009 | $0.00522 |
Grade A, and why
concept-synthesis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 514 lines — stays where its author put it; the contents beside it link to each section on GitHub.
concept-synthesis — From Raw Stubs to Intellectual Map
Convention: see conventions/quality.md for back-link enforcement and quote-fidelity requirements.
Convention: see _brain-filing-rules.md — output files under
concepts/per the primary-subject rule.
What this solves
Many ingestion pipelines (signal-detector, idea-ingest, voice-note-ingest) create a concept page for every idea mentioned. Over months this produces:
- Thousands of stub pages, many duplicates or near-duplicates
- Timeline entries that repeat the same source across multiple concept pages
- No synthesis — just "the user mentioned X on this date"
- No tier assignments — everything flat
- No clustering — related ideas aren't linked
This skill transforms that raw material into a curated intellectual map.
Architecture
Phase 1: Dedup + merge (deterministic)
N stubs → ~N/4 canonical concepts
├── Jaccard dedup (word-overlap on titles + first-paragraph)
├── Substring dedup ("founder mode" vs "founder mode vs manager mode")
├── Semantic dedup (LLM: "are these the same idea?")
└── Merge timelines + aliases from duplicates into the canonical page
Phase 2: Score + tier (deterministic + heuristic)
Each canonical concept → scored and tiered
├── Frequency: distinct sources referencing this concept
├── Timespan: first mention → last mention in days
├── Breadth: distinct months it appears in
├── Engagement: avg engagement on concept-bearing sources (if available)
└── Tier: T1 Canon | T2 Developing | T3 Speculative | T4 Riff
Phase 3: Synthesize (LLM, T1+T2 only)
T1 + T2 concepts → rich synthesis
├── Evolution narrative: how the idea sharpened over time
├── Best articulation: highest-engagement or most precise quote
├── Related concepts: cross-links to other concepts
├── Context: what was happening when this idea emerged / evolved
└── Counter-positions: what this idea argues against
Phase 4: Cluster + map (LLM)
All tiered concepts → intellectual clusters
├── Group related concepts into domains (auto-named via LLM)
├── Generate cluster summary pages
├── Build a master concepts/README.md with the full map
└── Identify idea genealogies (concept A → evolved into concept B)
Phase 5: Curation cull (rubric + reversible merge)
Each concept → hard verdict: ELITE | KEEP | MERGE/REWRITE | DELETE
├── 6-axis rubric (substance 2x, packaging 1x) + minimum substance gate
├── Grounding labels (VERIFIED / OPINION / NEEDS_SOURCE / UNSAFE)
├── Cluster budgets + reputational-risk gate
├── Merge-with-backlinks into cluster canonicals (fully reversible)
└── merge_count / independent_sources → emergent tier promotion
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 514 lines · 90 tokens per session scan A ed02d2e38514
concept-synthesis is a skill published in the GitHub repository garrytan/gbrain (29,668 stars, last pushed today), licensed MIT. It adds 90 tokens to every session and 5,218 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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