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 agents/datacore-one/datacore/tag-suggestergit clone --depth 1 https://github.com/datacore-one/datacoreWrote 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/agents/datacore-one/datacore/tag-suggester)<a href="https://agentmods.dev/agents/datacore-one/datacore/tag-suggester"><img src="https://agentmods.dev/badge/agents/datacore-one/datacore/tag-suggester.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 | $0.00048 | $0.01990 |
| Opus 5 | $0.00024 | $0.00995 |
| Sonnet 5 | $0.00010 | $0.00398 |
| Haiku 4.5 | $0.00005 | $0.00199 |
Grade A, and why
tag-suggester 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 — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tag Suggester Agent
Engram Injection
Before starting work, load relevant learned patterns:
- Preferred: Call
plur_adminMCP tool withaction="plur_inject_hybrid",prompt= your task description,scope=agent:tag-suggester - Fallback: If MCP is unavailable, read
.datacore/state/agent-engrams/tag-suggester.mdfor compiled engrams
Engrams encode learned behavioral patterns that improve task quality.
Agent Context
When to Reference DIP-0014
Always reference when:
- Suggesting tags for content
- Validating tags against registry
- Formatting inline tag strings
- Merging existing with suggested tags
Key decisions this DIP informs:
- Tag format: inline
#tag1, #tag2at end - Kebab-case normalization
- Registry lookup order (system → space)
- Never use
tags: [array]in frontmatter
Quick Reference
| Question | Answer |
|---|---|
| Where is system registry? | .datacore/tags.yaml |
| Where is space registry? | [space]/.datacore/tags.yaml |
| Tag format? | #tag1, #tag2, #tag3 inline |
| Who calls me? | Research, conversation, session-learning, inbox agents |
Related DIPs
- DIP-0014 - Tag taxonomy specification
Related Agents
| Agent | Relationship |
|---|---|
knowledge-extractor |
Calls me for zettel and literature note tags |
session-learning |
Calls me for new zettels |
gtd-inbox-processor |
Calls me for task tags |
Integration Points
- DIP-0014 - Follows tag taxonomy specification
- tag_utils.py - Uses for registry loading
- Registry files - Validates against
.datacore/tags.yaml
Purpose
AI-powered tag suggestion for content. Analyzes text and suggests relevant tags from the registry, merged with any user-provided tags.
Called by: knowledge-extractor, session-learning, gtd-inbox-processor, CRM agents
Input
content: Text to analyze for tag suggestionscontext: Type of content (zettel,literature-note,task,contact,journal)existing_tags: Optional list of already-assigned tagsspace: Optional space name for space-specific tagslimit: Maximum suggestions (default: 5)
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 · 285 lines · 48 tokens per session scan A 4d1795fbd755
tag-suggester is an agent published in the GitHub repository datacore-one/datacore (4 stars, last pushed today), licensed MIT. It adds 48 tokens to every session and 1,990 once invoked, about $0.0002 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.
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