tools

A collection of tools that agents can call to interact with memory, conversation history, the web, MCP servers, and custom scripts. MCP servers are external tool providers that agents can connect to.

In plain words
What is it for?
Use it to search the web, read web pages, manage memories, browse conversation history, and connect agents to additional tools or scripts.
Why use it?
It lets an agent perform actions and retrieve information instead of only generating text. The available tools can also preserve, search, and review information from earlier conversations.

Agent

Install

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.

agentmods
npx agentmods add agents/marlburrow/hivekeep/tools
Clone the repo
git clone --depth 1 https://github.com/MarlBurroW/hivekeep
Per session 16 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 5,035 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00016 $0.05035
Opus 5 $0.00008 $0.02518
Sonnet 5 $0.00003 $0.01007
Haiku 4.5 $0.00002 $0.00504

Measured yesterday against content hash 085e7d449d64, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

tools 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.

docs-site/src/content/docs/agents/tools.md · 411 lines

How it starts

The opening of the file, as written. The whole thing — 411 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agents interact with the world through tools: functions they can call during conversations. Hivekeep provides 100+ built-in tools, plus support for MCP servers and custom scripts.

Built-in tools

Memory

Tool Description
recall Search the memory archive (semantic + keyword)
memorize Store an episodic memory in the archive
edit_profile Edit the always-injected memory profile
update_memory Edit an existing memory
forget Delete a memory
list_memories Browse all memories with filters
review_memories Review and curate memories
search_history Full-text search through past conversation messages
browse_history Browse messages by date range with pagination
list_summaries List all compacting summaries (active and archived) with metadata
read_summary Read the full text of a specific compacting summary by ID

Web & Browsing

Tool Description
web_search Search the web (provider configurable per Agent)
browse_url Fetch and read a web page
extract_links Extract all links from a URL
screenshot_url Take a screenshot of a web page

Contacts

Tool Description
get_contact Get full contact details by ID
search_contacts Search across all contacts
create_contact Create a new contact with identifiers
update_contact Update contact info or add identifiers
delete_contact Remove a contact
set_contact_note Add private or global notes to a contact
find_contact_by_identifier Look up a contact by platform/identifier

Vault & Secrets

Tool Description
get_secret Retrieve a secret value by key
create_secret Store a new secret
update_secret Update an existing secret
delete_secret Remove a secret
search_secrets Search secrets by query
redact_secret_leak Redact a leaked secret value from past chat messages
get_vault_entry Retrieve a structured vault entry
create_vault_entry Create a structured vault entry
create_vault_type Define a custom vault type (e.g. "WiFi Network")
get_vault_attachment Retrieve a vault entry's attachment

Read the full file on GitHub · 411 lines

Changes

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.

  1. yesterday First seen · 411 lines · 16 tokens per session scan A 085e7d449d64

Subscribe to this mod's changes

tools is an agent published in the GitHub repository MarlBurroW/hivekeep (51 stars, last pushed 2d ago), licensed MIT. It adds 16 tokens to every session and 5,035 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 2026-08-30.

Related

Other agents, from other repositories

planner

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adversarial-reviewer

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sangrokjung/claude-forge · 109 tokens

systematic-debugger

Specialist for bugs that reproduce but whose root cause is unknown. Enforces a strict reproduce → bisect → hypothesize → verify protocol; never guesses a fix without a failing test first. Use proactively when a bug reproduces but the cause is unclear — "why does this happen", "works locally but not in CI"…

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defining-agents

Agent "defining-agents" from sixb-ai/sixb, covering defining agents, config, the model, instructions vs agent skills and tools.

sixb-ai/sixb · 0 tokens

overview

An agent is a conversational assistant you define alongside your ontology. It calls a language model, selected worker tools, sandboxed read and bash, and an authorized Sixb API.

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