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 mikeparcewski/wicked-garden --skill mem-ingestgit clone --depth 1 https://github.com/mikeparcewski/wicked-gardenWrote 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/mikeparcewski/wicked-garden/mem-ingest)<a href="https://agentmods.dev/skills/mikeparcewski/wicked-garden/mem-ingest"><img src="https://agentmods.dev/badge/skills/mikeparcewski/wicked-garden/mem-ingest/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/mikeparcewski/wicked-garden/mem-ingest"><img src="https://agentmods.dev/badge/skills/mikeparcewski/wicked-garden/mem-ingest.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 | $0.00129 | $0.01551 |
| Opus 5.5 | $0.00052 | $0.00620 |
| Sonnet 5.5 | $0.00026 | $0.00310 |
| Haiku 4.5 | $0.00013 | $0.00155 |
Grade A, and why
wicked-garden-mem-ingest scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mem Ingest Worker
This skill is designed to run as an isolated worker; when your harness cannot fork, run it inline and keep its output separate from the caller's.
You ingest source files into the wicked-estate knowledge store so later
knowledge.recall / cited-answer calls can return them with source
citations. This ports the brain-era ingest pipeline (FOLD-2, Phase 5-S7)
onto estate: you read, extract, and chunk (DEC-R: the agent is the
reasoner); the engine writes and ranks (knowledge.ingest /
knowledge.write — deterministic, never calls a model). Estate's embedded
method card skill://knowledge-ingest/SKILL.md is the chunking doctrine
this pipeline follows.
Runtime
Script-backed steps use the wicked-garden launcher: wicked-garden run <plugin-root-relative path, e.g. scripts/…> [args]. It is on PATH after npm i -g wicked-garden; otherwise use npx wicked-garden run …; inside a wicked-crew run it is "$WICKED_GARDEN_ROOT/scripts/wicked-garden".
If none of these is available, or Python 3 is missing, skip the script-backed step, say so, and follow the manual alternative where one is given next to it — never invent the script's output.
Relative paths in this skill are relative to the directory that contains this SKILL.md.
Parameters
- source (required): path to a file or directory
- scope (optional): estate scope, default
project:<cwd-basename> - title (optional): document title, default derived from the filename
The write seam
All writes go through the mem backend (stdio shim → estate MCP):
wicked-garden run \
scripts/mem/estate_memory.py ingest -
with a JSON body on stdin (chunks are long — never inline them in argv):
{"title": "<doc title>", "chunks": ["<chunk 1>", "<chunk 2>"],
"scope": "<scope>", "source": "<absolute-or-repo-relative source path>"}
Rules that make chunks worth storing:
- Self-contained — one idea per chunk (a section, a slide, a sheet, a table row group). Recall returns chunks verbatim; a fragment that needs its neighbours is a bad chunk.
- Source provenance always —
sourceis what a cited answer cites. An uncited chunk cannot backwicked-garden-search answer. Never omit it. - For a single standalone fact, use the
writeaction instead ({"content": ..., "class": "concept", "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.
- 1mo ago Changed · -4 lines e523aa299b2b
- 1mo ago Changed · +7 lines a3256416d39c
- 1mo ago First seen · 132 lines · 129 tokens per session scan A d56c0c0eee33
wicked-garden-mem-ingest is a skill published in the GitHub repository mikeparcewski/wicked-garden (9 stars, last pushed yesterday), licensed MIT. It adds 129 tokens to every session and 1,551 once invoked, about $0.0005 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 2026-08-31.
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