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 ThomasMoreAI/legal-skills-open --skill canada-memogit clone --depth 1 https://github.com/ThomasMoreAI/legal-skills-openWrote 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/thomasmoreai/legal-skills-open/canada-memo)<a href="https://agentmods.dev/skills/thomasmoreai/legal-skills-open/canada-memo"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/canada-memo/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/thomasmoreai/legal-skills-open/canada-memo"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/canada-memo.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 | $0.00066 | $0.00833 |
| Opus 5 | $0.00033 | $0.00417 |
| Sonnet 5 | $0.00013 | $0.00167 |
| Haiku 4.5 | $0.00007 | $0.00083 |
Grade A, and why
canada-memo 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 12d 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
canada-memo
The case_stressor pipeline produces a structured PI Case Assessment Memo backed by 340 real Ontario PI decisions. This skill is the agent's hook into that pipeline.
Trigger
Use this skill whenever the user's message starts with the word "Canada" / "canada" / "CANADA" (any case), with or without a comma after.
Examples that trigger:
Canada, my child was playing soccer outside Target and got hurtcanada slip and fall on icy sidewalk in TorontoCANADA: 55yo woman rear-ended on highway, soft tissue, treatment gapCanada — bicyclist hit by SUV in Ottawa
How to call
Strip the leading Canada (and any leading punctuation/whitespace) to get
the fact pattern, then call:
from openclaw.skills.canada_memo.client import generate_memo
memo_text = generate_memo(facts)
Or via shell from within the OpenClaw harness:
cd ~/Specter && python3 -m openclaw.skills.canada_memo.client \
"my child was playing soccer outside Target and got hurt"
The function returns a single markdown string. Print it verbatim as the
WhatsApp reply — do not summarize, do not paraphrase, do not add headers.
The memo already contains its own structure (PI CASE ASSESSMENT MEMO …).
What NOT to do
- Do not ask clarifying questions before running the memo. The corpus is fact-pattern-indexed; a thin query still returns useful comparables. The memo itself flags "facts not provided" gaps inside the WEAKEST POINTS section — let the memo do the asking.
- Do not call
harvester_query.searchfor Canadian queries that match this trigger — that would route to the small Canada vector slice without running the full memo (stats + Claude analysis + 3 key precedents). - Do not invent precedents. Everything the memo cites comes from real
CanLII data already in
case_stressor/chroma_db.
After the memo
The memo ends with:
TYPE "what if [changed fact]?" TO STRESS-TEST YOUR CASE
If the user's NEXT message starts with what if, route to the
/canada/whatif endpoint with the prior facts as original_facts and the
new message as modified_facts. (Future enhancement — for now the agent
can re-run the baseline memo with adjusted filters.)
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.
- 12d ago First seen · 94 lines · 66 tokens per session scan A 9f2bc1ab1563
canada-memo is a skill published in the GitHub repository ThomasMoreAI/legal-skills-open (72 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 66 tokens to every session and 833 once invoked, about $0.0003 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.
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