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 vbcherepanov/total-agent-memory --skill codex-skillgit clone --depth 1 https://github.com/vbcherepanov/total-agent-memoryWrote 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/vbcherepanov/total-agent-memory/codex-skill)<a href="https://agentmods.dev/skills/vbcherepanov/total-agent-memory/codex-skill"><img src="https://agentmods.dev/badge/skills/vbcherepanov/total-agent-memory/codex-skill/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/vbcherepanov/total-agent-memory/codex-skill"><img src="https://agentmods.dev/badge/skills/vbcherepanov/total-agent-memory/codex-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Rogue Agent · line 143 Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
- medium Excessive Agency · line 29 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00065 | $0.01241 |
| Opus 5.5 | $0.00026 | $0.00496 |
| Sonnet 5.5 | $0.00013 | $0.00248 |
| Haiku 4.5 | $0.00006 | $0.00124 |
Grade A, and why
memory 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 1mo 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 — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Persistent Memory System
You have access to a persistent cross-session memory via MCP tools. Knowledge survives between sessions and is shared across agents working on the same project.
Session Start
Always run these two calls before any work:
self_rules_context(project="<project>")
memory_recall(query="<current task description>", project="<project>")
If relevant knowledge is found, mention it briefly and apply it.
Auto-Save Rules
Save knowledge automatically -- never ask the user whether to save.
| Event | type | What to save |
|---|---|---|
| Architectural decision | decision |
Decision + WHY + rejected alternatives |
| Non-trivial bug fix | solution |
Symptom -> root cause -> fix |
| Gotcha or pitfall discovered | lesson |
Expected vs actual + takeaway |
| Infrastructure or config setup | fact |
Config details + key parameters |
| Project pattern established | convention |
Rule + code example |
| Session ending | fact |
Summary of what was done + what remains |
Format:
memory_save(
content="Concise, actionable description",
type="decision|solution|lesson|fact|convention",
project="<project>",
tags=["relevant", "tags"],
context="Why this matters. For decisions: always explain WHY."
)
Do NOT save: trivial edits, intermediate steps, information obvious from the code.
Error Logging
On any error (command failure, wrong assumption, API error, timeout), log it automatically:
self_error_log(
description="What went wrong",
category="code_error|logic_error|config_error|api_error|timeout|loop_detected|wrong_assumption|missing_context",
severity="low|medium|high|critical",
fix="How it was fixed (empty if unresolved)",
project="<project>"
)
When pattern_detected: true is returned (3+ similar errors), extract an insight:
self_insight(action="add", content="Generalized lesson", category="<error_category>", source_error_ids=[...])
Self-Improvement Pipeline
What ships with it
1 file 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.
- 1mo ago First seen · 155 lines · 65 tokens per session scan A 7095fa55c3d1
memory is a skill published in the GitHub repository vbcherepanov/total-agent-memory (73 stars, last pushed 5d ago), licensed MIT. It adds 65 tokens to every session and 1,241 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 2026-08-30.
Other skills, from other repositories
marm-init
Guided MARM MCP setup. Invoke after running marm-memory init on the CLI to configure MARM memory across your agent. Drives transport choice, runtime choice, MCP config writing, multi-agent linking, and server start. Works on Claude, Codex, Gemini, Qwen, Cursor, VS Code, and other MCP-capable agents.
engram-digest
Seed or top up this project's Engram graph from the existing codebase — an explicit, user-invoked digestion of the current working tree into typed memory nodes (decisions, principles, cautions, problems, insights, intents). Use when the user says "digest this project", "ingest the codebase into memory", "seed the…
engram
Read and write the project's durable reasoning memory (decisions, principles, cautions, problems, insights) through the Engram MCP tools. Recall relevant memory before non-trivial work; capture only durable, high-value knowledge silently at natural stopping points; keep the graph honest (judge suspects, close answered…
session-recap
Document Claude Code sessions by extracting knowledge into cross-referenced documentation. Triggers on "recap the session", "summarize the work", or after significant code changes.
garden-tending
Tend the knowledge garden — diagnose vault health, condense project memos into project.md overviews, create/merge cross-project topics, fix broken links, archive superseded notes, extend trails. Trigger on "tend the garden", "condense", "update project overview", "check vault health", "where are we with X?", "what…
knowledge-bank-lookup
Delegates knowledge bank lookups to Explore subagents with reflections-first strategy that learns from past mistakes. Checks /reflections/ directory before documentation to extract documented failures to avoid and proven approaches to apply. Automatically triggers when user mentions services ([project-a], [project-b]…