SKILL·CE3E00

memex

pjt222
Updated Yesterday
21
3
21
View on GitHub
Designaimcp

About

Memex is a cross-session memory system for agents that provides three key tools: loading a persistent bias-log at session start, searching prior context mid-session, and logging new observations. Its six-layer processing trail stores both facts and the agent's own reasoning patterns across multiple sessions. Developers should query Memex to avoid re-deriving prior architectural decisions, as such re-derivation indicates a gap in the memory trail.

Quick Install

Claude Code

Recommended
Primary
npx skills add pjt222/agent-almanac -a claude-code
Plugin CommandAlternative
/plugin add https://github.com/pjt222/agent-almanac
Git CloneAlternative
git clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/memex

Copy and paste this command in Claude Code to install this skill

Documentation

Memex

Agent-native shared memory. Postgres + pgvector index over a canonical markdown store, exposed over MCP. Lives at https://github.com/pjt222/memex.

When to Use

  • At session start, always. Call mcp__memex__recent_observations before substantive work. Loads the bias-log from prior sessions.
  • Mid-session, when about to make a non-trivial decision. Call mcp__memex__search "<topic>" to check whether the project has converged on this before.
  • Immediately when a bias surfaces in your own reasoning. Log an observation via mcp__memex__add while the context is fresh. Do NOT wait for session end.
  • When you catch yourself re-deriving something. Re-derivation IS the signal that the trail is incomplete; capture the gap as an observation and link to whatever you re-derived.

Inputs

  • Required: A registered memex MCP server in the active harness. Verify with claude mcp list | grep memex (Claude Code) or the equivalent in your harness.
  • Required: $MEMEX_PG_URL and $MEMEX_STORE_PATH in the server's environment.
  • Optional: $MEMEX_EMBED_PROVIDER=voyage + $VOYAGE_API_KEY for semantic / hybrid search. Without these, mode=keyword still works.

Procedure

Step 1: Load the bias-log

Before any substantive work in a fresh session, call:

mcp__memex__recent_observations(limit=20)

Read every returned entry. Each one is a pattern the agent (you, or a prior instance) noticed in its own reasoning. Recurring patterns are the most valuable; transient ones are still cheap to skim.

Expected: 5–30 observations covering biases (availability, confirmation, anchoring), pace tells (rushing past confusing measurements), and verification gaps (trusting summaries over source truth).

On failure: If the call fails with "tool not found", the MCP server isn't registered; run adapters/claude-code/install.sh (or the per-harness equivalent) from the memex repo first.

Step 2: Search before deriving

When a non-trivial decision approaches (architectural, naming, algorithmic), search first:

mcp__memex__search(query="<topic>", mode="hybrid", k=10)

For exact-wording lookups use mode=keyword. For purely conceptual queries (topic unlikely to share tokens with indexed text) use mode=semantic. Optional node_type filter restricts to one type (e.g. observation).

Expected: 0–10 hits. Even 0 hits is useful — it tells you the trail doesn't cover this decision, so your present reasoning becomes the canonical record.

On failure: If search errors (server down or db unreachable), fall back to the CLI substitute memex query "<topic>" --node-type observation (defaults to hybrid, which honors the type filter via its semantic leg). If it returns 0 hits on a topic that clearly should have coverage, treat the gap as a signal and proceed to Step 4.

Step 3: Log observations mid-session

When you notice a bias in your own reasoning:

mcp__memex__add(
  node_type="observation",
  title="<short bias name>",
  body="<context, mitigation, origin date>",
  tags=["bias-log", "vipassana"]
)

Body convention (mirroring docs/OBSERVATIONS.md in the memex repo; treat that file as the source of truth — it is read by an extractor):

<Description of the bias as it surfaced>. Mitigation: <what to do next time>. Origin: <date> + <context>.

Expected: the add call returns the new node's id (the CLI equivalent memex add prints <uuid>\t<store-path>) — confirmation the observation is in the canonical store.

On failure: rmcp dispatches tool calls concurrently — if add races a dependent call (add → link), await its response first. If the db is unreachable the write is lost; re-issue once the server is back, or fall back to appending the entry to docs/OBSERVATIONS.md by hand (Step 4).

Step 4: Surface unknowns

If recent_observations is empty (fresh memex install), or search returns nothing on a topic that clearly should have coverage, that's a documentary trail gap. Close it by appending to the canonical markdown and re-extracting, or by depositing directly via the MCP tool:

# Backfill path (run from the memex repo root):
$EDITOR docs/OBSERVATIONS.md   # append under "## Vipassana observations"
memex extract meditate-vipassana --registry extractors/sources.yml

Or use mcp__memex__add (Step 3) during the session to deposit the entry into the canonical store on the spot, without touching the file.

Expected: after extract, the new observation is queryable — memex query "<its topic>" --node-type observation returns it (the observation-node count grows by one).

On failure: extract is cwd-sensitive — run it from the memex repo root or pass --registry. If it reports "no new sources", the content hash already matched; confirm the append actually landed in docs/OBSERVATIONS.md.

Validation

  • mcp__memex__recent_observations returns ≥ 0 entries (call succeeded, not "tool not found")
  • Each substantive decision in the session is preceded by either a mcp__memex__search call or an explicit "no prior context to check" note
  • New biases noticed during the session are logged via mcp__memex__add before session end, not silently dropped
  • At session end, the agent has either committed new bias entries to docs/OBSERVATIONS.md or confirmed there are none worth logging

Common Pitfalls

  • Skipping the session-start call. The single highest-value use of memex. Skipping it is the strongest tell that the agent is treating each session as starting from scratch.
  • Logging at session end only. Biases caught at session end are reconstructed from memory and lose specificity. Log them immediately when they surface.
  • Logging an observation that's actually a concept. Bias-log entries are about the agent's own reasoning patterns. Reusable architectural facts belong in concept nodes.
  • Trusting search results over reading them. A title that matches your query isn't proof the body answers it. Fetch the full body with mcp__memex__get when in doubt.
  • Pipelining dependent MCP calls in one session. rmcp dispatches tool calls concurrently. If a later call depends on a write from an earlier call (add → link → neighbors), await each response before issuing the next.

Related Skills

  • memex-init — session-start ritual that wires memex into a fresh session; run it before this umbrella's Step 1 to register the server and load the bias-log.
  • memex-observe — the focused wrapper for Step 3; use it when the task is purely "log a bias I just noticed" rather than the full umbrella flow.
  • memex-wrap — session-close counterpart; confirms observations are logged (deferring the actual write to memex-observe) and writes the continuation trail this skill reads next session.
  • memex-verify — pre-commit gate for the memex repo itself; run it before committing changes to memex (cargo fmt / clippy / test).
  • breathe — pair with memex at session boundaries: breathe to release prior-session residue, then recent_observations to load the next-session priors.
  • meditate — full reflective close; outputs new observations worth logging via mcp__memex__add.
  • read-continue-here — complementary; loads project-state pickup doc. Memex loads cross-project bias-log; CONTINUE_HERE loads project-specific milestone state.

GitHub Repository

pjt222/agent-almanac
Path: i18n/de/skills/memex
0
agentsagentskillsai-assisted-developmentclaude-codeskillsteams
FAQ

Frequently asked questions

What is the memex skill?

memex is a Claude Skill by pjt222. Skills package instructions and resources that Claude loads on demand, so Claude can perform memex-related tasks without extra prompting.

How do I install memex?

Use the install commands on this page: add memex to Claude Code as a plugin, or clone its repository into your skills directory, then restart Claude so it picks up the skill.

What category does memex belong to?

memex is in the Design category, tagged ai and mcp.

Is memex free to use?

Yes. memex is listed on AIMCP and free to install. It runs inside Claude, so no separate service account is required to use the skill itself.

Related Skills

executing-plans
Design

Use the executing-plans skill when you have a complete implementation plan to execute in controlled batches with review checkpoints. It loads and critically reviews the plan, then executes tasks in small batches (default 3 tasks) while reporting progress between each batch for architect review. This ensures systematic implementation with built-in quality control checkpoints.

View skill
requesting-code-review
Design

This skill dispatches a code-reviewer subagent to analyze code changes against requirements before proceeding. It should be used after completing tasks, implementing major features, or before merging to main. The review helps catch issues early by comparing the current implementation with the original plan.

View skill
connect-mcp-server
Design

This skill provides a comprehensive guide for developers to connect MCP servers to Claude Code using HTTP, stdio, or SSE transports. It covers installation, configuration, authentication, and security for integrating external services like GitHub, Notion, and custom APIs. Use it when setting up MCP integrations, configuring external tools, or working with Claude's Model Context Protocol.

View skill
web-cli-teleport
Design

This skill helps developers choose between Claude Code Web and CLI interfaces based on task analysis, then enables seamless session teleportation between these environments. It optimizes workflow by managing session state and context when switching between web, CLI, or mobile. Use it for complex projects requiring different tools at various stages.

View skill