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 agentmods add commands/eddiebelaval/squire/memory-ingestgit clone --depth 1 https://github.com/eddiebelaval/squireWrote 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/commands/eddiebelaval/squire/memory-ingest)<a href="https://agentmods.dev/commands/eddiebelaval/squire/memory-ingest"><img src="https://agentmods.dev/badge/commands/eddiebelaval/squire/memory-ingest.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00688 |
| Opus 5 | $0.00000 | $0.00344 |
| Sonnet 5 | $0.00000 | $0.00138 |
| Haiku 4.5 | $0.00000 | $0.00069 |
Grade A, and why
memory-ingest 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 yesterday.
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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/memory-ingest -- File Insights Back Into Memory
You capture valuable analysis, discoveries, or decisions from the current conversation and file them into the MEMORY.md wiki AND MemPalace verbatim store. This is the "query results file back" pattern: good answers shouldn't disappear into chat history.
Arguments: $ARGUMENTS
Route by Arguments
| Input | Action |
|---|---|
"<topic>" |
File the current conversation's insights about this topic |
--session |
File a session summary (end-of-session compaction) |
--decision "<what>" |
File a specific decision with context and rationale |
| (empty) | Interactive: ask what to file |
Process
Step 1: Extract
From the current conversation, extract:
- Facts learned (new information about projects, people, tools)
- Decisions made (with rationale and alternatives considered)
- Discoveries (patterns, connections, insights)
- Corrections (things we got wrong and fixed)
Step 2: Classify
For each extracted item, determine:
- Memory type: user | feedback | project | reference
- Target file: existing memory file to UPDATE, or new file to CREATE
- Staleness risk: will this be stale in days, weeks, or months?
Step 3: File to MEMORY.md Layer
For each item:
If updating existing file:
- Read the target file
- Integrate new information (don't duplicate, merge)
- Update the frontmatter description if scope changed
- Verify MEMORY.md index entry still accurate
If creating new file:
- Write file with proper frontmatter (name, description, type)
- Follow body structure for type (feedback: rule + Why + How to apply; project: fact + Why + How to apply)
- Add entry to MEMORY.md index under correct section
- Keep index entry under 150 chars
Step 4: File to MemPalace Layer
For each item, also store the verbatim conversation context in MemPalace:
mempalace add_drawer --wing eddie_memory --room <appropriate_room> --content "<verbatim context>"
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.
- yesterday First seen · 93 lines · 0 tokens per session scan A 97dbf4594f99
memory-ingest is a command published in the GitHub repository eddiebelaval/squire (21 stars, last pushed 20d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 688 tokens. 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 2026-09-03.
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Nightly memory consolidation — prunes stale entries, merges duplicates, resolves contradictions, rebuilds MEMORY.md index. Use when memory files have accumulated over many sessions and need cleanup. Do NOT use for storing new decisions (use remember) or searching memory (use memory).
context-health
Dashboard de salud del contexto activo con predicción de degradación y recomendaciones de compactación. Usa cuando el usuario dice "context health", "salud del contexto", "degradation", "compactar contexto", "context overflow", "tokens", "session health", "compact", "contexto lleno". Monitorea degrdación del contexto…
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Capturar ideas y notas sin interrumpir el flujo de trabajo. Usa cuando el usuario dice "capturar idea", "quick note", "nota rápida", "grab this", "take a note", "guardar idea", "note to self", "capture thought", "I should remember", "guardar esto". Guarda en memoria persistente sin romper el contexto actual.