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 t-rhex/obsidian-mcp-server --skill obsidian-task-orchestrationgit clone --depth 1 https://github.com/t-rhex/obsidian-mcp-serverWrote 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/t-rhex/obsidian-mcp-server/obsidian-task-orchestration)<a href="https://agentmods.dev/skills/t-rhex/obsidian-mcp-server/obsidian-task-orchestration"><img src="https://agentmods.dev/badge/skills/t-rhex/obsidian-mcp-server/obsidian-task-orchestration/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/t-rhex/obsidian-mcp-server/obsidian-task-orchestration"><img src="https://agentmods.dev/badge/skills/t-rhex/obsidian-mcp-server/obsidian-task-orchestration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00115 | $0.02533 |
| Opus 5 | $0.00057 | $0.01267 |
| Sonnet 5 | $0.00023 | $0.00507 |
| Haiku 4.5 | $0.00012 | $0.00253 |
Grade A, and why
obsidian-task-orchestration 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 10d 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 — 253 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Obsidian Task Orchestration
Drive multi-agent task workflows through an Obsidian vault. Tasks are markdown notes with structured YAML frontmatter. The vault is the single source of truth — no external database, no API. Agents read, claim, update, and complete tasks through MCP tools.
This skill covers three roles: Worker (claim and execute tasks), Manager (create projects, monitor progress, handle failures), and Assistant (vault queries, daily notes, organization). All roles share a context-first discipline: start every session by calling get_context.
Start Every Session Here
get_context()
This returns a structured briefing: active projects, in-progress work, pending tasks, blockers, failures, recent decisions, recent discoveries, and pinned context notes. Read it before doing anything else. If you're focused on a specific project:
get_context(project_id: "proj-2026-03-09-xyz789")
MCP Tools Reference
Context & Knowledge Tools
| Tool | Purpose | Key Parameters |
|---|---|---|
get_context |
Session briefing — active work, blockers, recent decisions/discoveries | project_id?, hours? (default: 48) |
log_decision |
Record an architectural/design decision with rationale | title, context, decision, alternatives?, consequences? |
log_discovery |
Record a gotcha, TIL, or finding for future agents | title, discovery, impact?, recommendation?, category? |
Task Tools
| Tool | Purpose | Key Parameters |
|---|---|---|
create_task |
Create a task note | title, description, priority, type, depends_on, scope, acceptance_criteria |
list_tasks |
Query tasks by filters | status, priority, type, assignee, project, exclude_projects |
claim_task |
Atomically claim a pending task | task_id, assignee |
update_task |
Update status, append to agent log | task_id, status, log_entry |
complete_task |
Mark done with deliverables | task_id, deliverables, summary, status (completed/failed) |
create_project |
Create project with sub-tasks | title, description, tasks[] with depends_on_indices |
get_project_status |
Rollup progress and blockers | project_id |
What ships with it
5 files 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.
- 10d ago First seen · 253 lines · 115 tokens per session scan A 2f669d20af44
obsidian-task-orchestration is a skill published in the GitHub repository t-rhex/obsidian-mcp-server (2 stars, last pushed 6mo ago), licensed MIT. It adds 115 tokens to every session and 2,533 once invoked, about $0.0006 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 2026-08-31.
Other skills, from other repositories
project-sync
On-demand AI-powered sync of a project's repo state into the brain vault. Reads live git/GitHub/Jira data, updates the project status doc, and makes targeted edits to relevant brain docs where content is clearly stale. Triggered by "/project-sync [name]", "sync [project]", "what's the current state of [project]".
llm-wiki
Build and maintain a persistent, interlinked Obsidian-compatible markdown wiki using Karpathy's LLM Wiki pattern. Extension-backed with auto-generated metadata, guardrails, and 14 custom tools (+3 opt-in agent-trajectory tools).
link-memory
Use after important user-approved decisions, when durable context should be proposed or reviewed, and for explicit Link memory lifecycle work: remember, recall, review, update, archive, restore, forget, or explain local memories through the CLI without requiring MCP.
link-retrieve
Use before answering work that may depend on user memory, project history, source-backed notes, or prior decisions; retrieve compact Link context through the CLI without loading the whole wiki or requiring MCP.
link-ingest
Use when raw files are present, source pages look stale, or a user asks to ingest notes into Link; refresh source-backed wiki pages, propose memories, and validate updates through the CLI without MCP.
alive-bundle
Create, manage, and graduate bundles -- the unit of focused work within a walnut.