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GRU953GRU953/MTA_Plugin/skills/memorise/SKILL.md

memorise

Skill1 starsChanged 5 months agoMITView on GitHub

Digest a folder of documents into local, token-free knowledge-graph memory and recall from it. Use when the user wants to "memorise", "digest", "ingest", or "remember" files/attachments/a folder, build a knowledge graph from documents, or ask questions grounded in their own documents without paying tokens to read them. Triggers on "memorise these files", "digest my documents", "build memory from this folder", "remember this PDF", "what do my docs say about X".

1 other project uses a version of this.

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  • Other versions1 project uses a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 1

    1. jmylchreest/aide★ 19same name

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repositoryOne other file it gives its agents.

The file

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 2 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Never: read the converted documents back into the conversation — that defeats the token-free design.

    line 43
  2. Distinctive:

    Always cite source document names from recall hits when answering.

    line 45
  3. Very specific:

    If a project has no memory yet, run digest first.

    line 46
  4. Very specific:

    Use a project name to keep separate, reusable memories per body of work.

    line 47

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Memorise them All

Turn any pile of documents into local, token-free graph memory for Claude, and recall from it cheaply. All conversion and digestion runs on the user's machine (MarkItDown, plus optional Tesseract OCR) — fully deterministic and model-free, no LLM/Ollama/GPU. Claude only ever issues a small tool call and gets back compact metadata or a tiny relevant slice — never whole documents.

When to use

  • The user wants to ingest/digest/memorise files, attachments, or a whole folder.
  • The user asks a question that should be answered from their own documents.
  • The user wants a knowledge graph of their documents.

How it works (the pipeline)

  1. Convert — every attachment → Markdown locally (PDF/Office/HTML via MarkItDown, incl. legacy binary .doc/.ppt/.xls via optional LibreOffice; scanned images via optional Tesseract OCR; archives unpacked safely). Legacy Bengali typed in Bijoy/SutonnyMJ ANSI fonts is auto-upgraded to Unicode (font-aware, so mixed English+Bengali documents convert cleanly).
  2. Segment → Extract — structure-aware chunks; rule-based, deterministic extraction of entities, relations, and atomic facts (no LLM/model).
  3. Graph + themes — a knowledge graph with community-detected themes.
  4. Layered memory — a global synopsis, per-theme summaries, per-document notes, and graph.json. Recall ranks with model-free BM25 (Bengali-aware) and returns a tiny cited slice, declining off-topic queries.

Tools

  • digest(paths, project?, reset?) — build/refresh memory (reset: true rebuilds from scratch). Returns metadata only.
  • convert(paths, out_dir?, project?) — convert files/dirs/globs to Markdown locally (legacy Bengali/SutonnyMJ → Unicode); writes .md files to out_dir (default markdown_converted/ beside the input). Token-free. Use when the user just wants Markdown, not a digest.
  • recall(query, project?, k?) — return a small, citable slice of memory.
  • memory_overview(project?) — synopsis + themes.
  • export_memory(dest, project?) — export portable Markdown files.
  • list_digestible(directory) — list convertible files (paths/sizes only).
  • forget(project?) — delete a project's memory (graph, converted Markdown, summaries/notes). Irreversible.
  • memory_status() — local stack health.

Rules

  • Never read the converted documents back into the conversation — that defeats the token-free design. Trust the metadata and recall slices.
  • Always cite source document names from recall hits when answering.
  • If a project has no memory yet, run digest first.
  • Use a project name to keep separate, reusable memories per body of work.

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