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 markmhendrickson/neotoma --skill store-datagit clone --depth 1 https://github.com/markmhendrickson/neotomaWrote 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/markmhendrickson/neotoma/store-data)<a href="https://agentmods.dev/skills/markmhendrickson/neotoma/store-data"><img src="https://agentmods.dev/badge/skills/markmhendrickson/neotoma/store-data/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/markmhendrickson/neotoma/store-data"><img src="https://agentmods.dev/badge/skills/markmhendrickson/neotoma/store-data.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00020 | $0.00506 |
| Opus 5 | $0.00010 | $0.00253 |
| Sonnet 5 | $0.00004 | $0.00101 |
| Haiku 4.5 | $0.00002 | $0.00051 |
Grade A, and why
store-data 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 7d 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.
What it actually says
Store Data in Neotoma
When to use
When the user wants to persist structured data (contacts, tasks, events, transactions, notes, etc.) or files (PDFs, CSVs, images) into Neotoma's memory layer.
Workflow
-
Check for existing records before storing to avoid duplicates.
- Use
retrieve_entity_by_identifierfor names, emails, or identifiers. - Use
retrieve_entitieswith entity_type filter for related records.
- Use
-
Extract entities from the user's message or attached files.
- Use descriptive
entity_typevalues (contact, task, event, transaction, receipt, note, etc.). - Include ALL fields from the source data; unknown fields go to raw_fragments automatically.
- Use descriptive
-
Store with a single call when possible.
- Use the MCP
storetool for entities-only, file-only (bytes → content-addressed source row), or combined file + entities + optionalinterpretation. - Always include
idempotency_keyfor replay safety.
- Use the MCP
-
Link related entities using
create_relationship.- PART_OF: message belongs to conversation, item belongs to container.
- REFERS_TO: message references an entity.
- EMBEDS: container holds an asset (file).
- SUPERSEDES: new version replaces old.
-
Confirm storage using memory-related language ("stored in memory", "will remember").
Entity type discovery
Before inventing a new entity_type, check what schemas already exist:
- Use
list_entity_typeswith a keyword search. - If no match, use a descriptive snake_case type; Neotoma auto-creates the schema.
Required fields
idempotency_key: unique per store call (e.g.conversation-{id}-{turn}-{timestamp})entity_type: descriptive type for each entity- All source fields: include everything, not just known schema fields
Do not
- Skip the duplicate check for named entities (people, companies, places).
- Omit fields from source data because they are not in the schema.
- Store without an idempotency_key.
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.
- 7d ago First seen · 57 lines · 20 tokens per session scan A 21c4cf6bf2f8
store-data is a skill published in the GitHub repository markmhendrickson/neotoma (32 stars, last pushed yesterday), licensed MIT. It adds 20 tokens to every session and 506 once invoked, about $0.0001 per session on Opus 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 2026-09-03.
Other skills, from other repositories
remember
Routes user requests containing "remember", "recall", "checkpoint", "session", "todo", or "where were we" to the correct OpenEmpiric (OEM) MCP tool. Use when the user wants to persist, retrieve, or contextualize knowledge from project memory.
akf
Trust metadata for files, memories, and skills — check before you trust, stamp what you verify. A stamp costs 15 tokens; re-verifying costs 15,000.
akf
Trust metadata for files, memories, and skills — check before you trust, stamp what you verify. Use before building on existing files, after completing verified work, and when handling agent memories or downloaded skills.
aoa-memo
AoA/Abyss durable memory and owner orientation: use when ongoing work may depend on reviewed prior decisions, provenance, lifecycle/currentness, or an existing memo artifact, even when none is named. Also use to recall, review, or evolve a candidate, export, quarantine packet, object, corpus identity, lifecycle…
soul-archive
Soul Archive — A digital personality persistence system + agentic memory. Builds your digital soul clone through everyday AI conversations, with proactive context injection, cross-session recall, failure-pattern warning, and pattern distillation. All data stored locally as plaintext JSON. Six modes: Soul Extract, Soul…
mk:wiki
Capture, gate, query, and render long-term project knowledge through the gated mewkit wiki subsystem. Use to create a wiki, propose/approve candidates (scanner-gated), hand off a skill's terminal artifact as a scanned candidate, recall context, search the FTS index, or list pages. Agents may only PROPOSE candidates…