Honcho is a memory service for software agents that stores messages and events, builds representations of people and other entities over time, and provides session context, search results, and natural-language insights. It is for developers building agents that need persistent, changing state across conversations and projects, using a managed service, local stack, or self-hosted FastAPI server. The catalogue entries connect coding agents and MCP clients to Honcho’s memory system.
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 plastic-labs/honcho --skill property-reprogit clone --depth 1 https://github.com/plastic-labs/honchoWrote 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/plastic-labs/honcho/property-repro)<a href="https://agentmods.dev/skills/plastic-labs/honcho/property-repro"><img src="https://agentmods.dev/badge/skills/plastic-labs/honcho/property-repro/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/plastic-labs/honcho/property-repro"><img src="https://agentmods.dev/badge/skills/plastic-labs/honcho/property-repro.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00074 | $0.01454 |
| Opus 5.5 | $0.00030 | $0.00582 |
| Sonnet 5.5 | $0.00015 | $0.00291 |
| Haiku 4.5 | $0.00007 | $0.00145 |
Grade A, and why
property-repro scanned grade A with 1 finding 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 today.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
A failure prints the exception type and a curl command for the shrunk request. The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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.
- today First seen · 95 lines · 74 tokens per session scan A 678be42969a4
property-repro is a skill published in the GitHub repository plastic-labs/honcho (7,793 stars, last pushed today), licensed AGPL-3.0. It adds 74 tokens to every session and 1,454 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-28.
Other skills, from other repositories
debug-with-memlog
Systematically investigate bugs, errors, test failures, build failures, deployment failures, regressions, performance problems, and unexpected behavior with prior Memlog lessons. Use before proposing fixes, especially after a previous fix failed.
systematic-debugging
4-phase root cause debugging: understand bugs before fixing.
module-regression
Govern cross-module regression in large repositories with a REGRESSION.md ledger that records each module's downstream consumers and executable acceptance command. After a change, run the changed module and every affected downstream command, and use observed exit codes as regression evidence under the project's…
fix-failing-tests
Diagnose a failing test in the googleapis/mcp-toolbox repo and land a fix by reasoning from the actual error: read the failure, reproduce it, shrink it until the cause is forced into the open, then fix the cause. Use this whenever a test or CI job is red, a build breaks after a change, many packages fail at once, or a…
reproduce-bug
Reproduce a reported bug in googleapis/mcp-toolbox and decide whether it is real, delivering an evidence-backed verdict: confirmed, already fixed, misconfiguration, client-side, works as intended, not reproducible, or blocked. Use whenever a maintainer asks you to reproduce, verify, confirm, or investigate a bug…
credit-note-fixer
Fix the tiny credit-note formatting bug and rerun the exact targeted test command.