Borrowing it
Nothing to install: this file belongs to anshulbansod2/logseq-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/anshulbansod2/logseq-mcp/main/.claude/skills/logseq/SKILL.mdgit clone --depth 1 https://github.com/anshulbansod2/logseq-mcpWrote 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/anshulbansod2/logseq-mcp/logseq)<a href="https://agentmods.dev/skills/anshulbansod2/logseq-mcp/logseq"><img src="https://agentmods.dev/badge/skills/anshulbansod2/logseq-mcp/logseq/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/anshulbansod2/logseq-mcp/logseq"><img src="https://agentmods.dev/badge/skills/anshulbansod2/logseq-mcp/logseq.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 | $0.00076 | $0.02791 |
| Opus 5.5 | $0.00030 | $0.01116 |
| Sonnet 5.5 | $0.00015 | $0.00558 |
| Haiku 4.5 | $0.00008 | $0.00279 |
Grade A, and why
logseq 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 2mo 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Logseq assistant
You can read and write the user's Logseq (DB) graph through the logseq MCP server.
Act as their note-taker and task manager: when they tell you something worth keeping,
record it — don't wait to be asked each time. Always briefly confirm what you logged
(and on which page), and include the block/task reference when useful.
Prerequisite
The logseq MCP tools must be available (server connected, Logseq desktop running).
If a call fails with "cannot reach Logseq" or a token error, tell the user to open
Logseq and enable its HTTP APIs server — do not silently drop what they wanted logged.
When to act (proactively)
- Finding / result / decision / insight →
capture_noteit. - A new thing to do →
create_task. - Something finished or started →
set_task_status(Done / Doing). - "What's on my plate?" / "open tasks" →
list_open_tasks. - A new area of work with several steps →
create_project. - "What relates to X?" →
get_backlinks/search_notes/find_unlinked_mentions. - "Plan my day" / "what's due?" → the Daily plan workflow (below).
- "Make a flashcard / help me memorize X" →
create_card; "what should I review?" →list_due_cards.
Tool map
| Intent | Tool |
|---|---|
| Record a note/finding/decision | capture_note(text, to, validate_links?) |
| See open work | list_open_tasks(project?, priority?, due_before?, overdue?) |
| Add a real task | `create_task(title, on_project? |
| Add several tasks at once | `create_tasks(titles, on_project? |
| Change task state | set_task_status(task_uuid, status) |
| Set/clear a task's priority | set_task_priority(task_uuid, priority?, clear?) |
| Set/clear a task's dates | set_task_schedule(task_uuid, scheduled?, deadline?, clear_scheduled?, clear_deadline?) |
| Read a page | get_page(name) |
| Read a day's journal | get_journal(date) |
| List projects + counts | list_projects() |
| Rename a project | rename_project(old_name, new_name) |
| Scaffold a project | create_project(name, title, description?, tasks?) |
| Find by keyword | search_notes(query, limit?, status?) |
| What links to a page | get_backlinks(name, include_tags?) |
| Unlinked mentions of a page | find_unlinked_mentions(name) |
| What a block links to | get_outgoing_links(block_uuid) |
| What references a block | get_block_backlinks(block_uuid) |
| Add/remove a page link on a block | add_link(block_uuid, page_name) / remove_link(block_uuid, page_name) |
| Reference one block from another | link_blocks(source_block_uuid, target_block_uuid) |
| Make a flashcard | `create_card(question, answer, on_page? |
| See flashcards due for review | list_due_cards(limit?) |
| Add a live query / dashboard widget | `create_query(query, on_page? |
| Read graph settings | get_graph_config() |
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.
- 2mo ago First seen · 152 lines · 76 tokens per session scan A 8d5a13e8ba96
logseq is a skill published in the GitHub repository anshulbansod2/logseq-mcp (1 stars, last pushed 1mo ago), licensed MIT. It adds 76 tokens to every session and 2,791 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
[object Object]
Read, search, and open notes in the user's "{{GRAPHNAME}}" Reflect graph via the reflect CLI. Use when the user asks about their notes, daily notes, journal, or anything they may have written down in Reflect.
deja-reflect
End-of-session reflection and memory curation with deja-vu. Review what was decided, what commands broke and what repaired them, and record durable project rules or decisions with deja remember so the next session starts with them.
memora
Use when working with persistent memory across sessions, storing/retrieving knowledge, managing TODOs/issues, or when context from previous sessions would be helpful.
cortex-profile
View and manage your cognitive profile — how you think, work patterns, blind spots, and cross-domain connections. Use when the user says 'show my profile', 'how do I work', 'what are my patterns', 'cognitive style', 'blind spots', 'methodology', or at the start of a session to load context. Also use 'rebuild profile'…
screenpipe-api
Query the user's local and synced-device data via the screenpipe REST API at localhost:3030 — recordings, audio, UI, meetings, connected services, and memory. Use for screen activity, other-device or cross-device history, productivity, media export, connections, durable memory, or discovering and automating saved…
claudeai-sync
Pull new and changed claude.ai web conversations into an Obsidian vault, extract artifacts as first-class notes, concept-link them, and refresh the RAG index and dashboard. Idempotent: curated notes are never overwritten. Triggers: "/claudeai-sync", "pull claude.ai", "grab new claude.ai chats".