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
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add garrytan/gbrain --skill daily-task-managergit clone --depth 1 https://github.com/garrytan/gbrainWrote 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/daily-task-manager)<a href="https://agentmods.dev/skills/garrytan/gbrain/daily-task-manager"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/daily-task-manager/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/garrytan/gbrain/daily-task-manager"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/daily-task-manager.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00046 | $0.02181 |
| Opus 5.5 | $0.00018 | $0.00872 |
| Sonnet 5.5 | $0.00009 | $0.00436 |
| Haiku 4.5 | $0.00005 | $0.00218 |
Grade A, and why
daily-task-manager 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 16d 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 — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Daily Task Manager
Contract
This skill guarantees:
- Tasks stored as a brain page (
ops/tasks.md) with structured format and a stableidper task - Task lifecycle: add → in-progress → complete | defer | remove
- Priority levels: P0 (urgent), P1 (today), P2 (this week), P3 (backlog)
- Completed tasks archived with completion date; deferred tasks carry a target date + reason
- Mutations never drop unrelated tasks or unknown sections
- Every action returns the structured result below (Returns)
Returns
After every action, report a structured result so callers (including sub-agents) can chain reliably:
{action, task_id, status: ok|not_found|ambiguous|needs_confirmation, priority, date, page: "ops/tasks.md", saved: true|false}
For review, return the grouped active-task list instead of a single task_id. When invoked with the trigger "task list json", return a JSON array of task objects {id, description, priority, due, status} instead of markdown.
Tool Interface
Use ONLY the declared tools. get_page("ops/tasks.md") to read, put_page("ops/tasks.md", …) to write, add_timeline_entry for the audit trail, search for cross-referencing. Do not shell out to gbrain CLI verbs from this skill; the tools are the interface. (When the user runs this manually outside an agent, the CLI equivalents are gbrain get ops/tasks / gbrain put ops/tasks — equivalents only, not the skill's interface.)
Action Routing
Map user intent deterministically before touching state:
- "add / remind me to / put X on my list" → add
- "done with X / finished X / completed X / ✅ X" → complete
- "push X / defer X / move X to next week" → defer
- "delete X / remove X / kill task X" → remove (explicit delete words only — never infer remove)
- "what are my tasks / task list / what's on my plate (today)" → review ("today" filters to P0+P1)
Phases
- Load.
get_page("ops/tasks.md"). First run: if the page does not exist, create it from the Output Format template, then proceed. - Validate. Determine the action via Action Routing. If required fields are missing (see per-action rules), ask ONE concise clarification before mutating state. Never fabricate priorities, due dates, or defer reasons.
- Identify the target task (complete/defer/remove): match by
idwhen given; otherwise fuzzy-match description against ACTIVE tasks only. Zero matches → returnnot_found, do not mutate. Multiple matches → list candidates with IDs, returnambiguous, do not mutate. - Execute:
- Add: Require a description. Priority: use the user's stated/clearly-implied level; otherwise default to P3 and say so in the reply + timeline entry. Due date only if supplied or explicit in the user's words. Mint a new task ID (
t-YYYYMMDD-NN, NN = next free ordinal that day). Add a timeline entry. - Complete: Mark
[x], move to Completed with(completed: YYYY-MM-DD). - Defer: Require a target date/timeframe AND a reason; ask if missing. Move to Deferred preserving original text, ID, and priority unless the user changes them.
- Remove: Destructive — require explicit confirmation unless the user's message already contains it. Prefer suggesting complete or defer.
- Review: Read-only. Never mutates. Active tasks grouped by priority, IDs shown.
- Add: Require a description. Priority: use the user's stated/clearly-implied level; otherwise default to P3 and say so in the reply + timeline entry. Due date only if supplied or explicit in the user's words. Mint a new task ID (
- Save.
put_page("ops/tasks.md")after any mutation. Diff-mindset: touch only the affected lines; preserve all other content, including sections this skill doesn't recognize.
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.
- 16d ago Changed f77c08ae1f40
- 17d ago Changed · +1 lines 89b54d11aabe
- 19d ago Changed · +8 lines cbec93c0d908
- 1mo ago First seen · 133 lines · 46 tokens per session scan A a0e019eb2b0c
daily-task-manager is a skill published in the GitHub repository garrytan/gbrain (31,098 stars, last pushed today), licensed MIT. It adds 46 tokens to every session and 2,181 once invoked, about $0.0002 per session on Opus 5.5. 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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