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 skills/realactivity/tula/memory-diffnpx skills add realactivity/tula --skill memory-diffgit clone --depth 1 https://github.com/realactivity/tulaWhat 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 | $0.00105 | $0.01183 |
| Opus 5 | $0.00053 | $0.00592 |
| Sonnet 5 | $0.00021 | $0.00237 |
| Haiku 4.5 | $0.00011 | $0.00118 |
Grade A, and why
memory-diff 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
memory-diff
When to Use
✅ Use when:
- User asks "what's changed in my health since <last week / last month / since X>"
- Post-visit or post-lab summaries - "what's new since my last appointment"
- Scheduled weekly or monthly longitudinal check-ins
- "Since I started " or "since my referral to " recaps
- Another skill needs a "what's new" sub-step (e.g., after
health-recordsrefresh)
When NOT to Use
❌ Don't use when:
- User wants news or social signal -> use
myhealth-pulse - User shares a PDF, screenshot, or image -> use
med-pdf - User asks for raw chart data -> use
health-records - User wants to draft a clinician message -> use
epic-note - User asks for medical advice - decline politely; this reads memory, not clinical judgment
Setup
No external tools, no API keys. The skill reads from the local workspace only.
Memory sources, in precedence order (full contract in
references/memory-paths.md):
~/.openclaw/workspace/.health-records-cache/<date>/- structured FHIR JSON~/.openclaw/workspace/.med-pdf-cache/<slug>/- extracted JSON from PDFs~/.openclaw/workspace/memory/*.md- dated agent notes~/.openclaw/workspace/MEMORY.md- persistent agent memory~/.openclaw/workspace/.myhealth-pulse-cache/<date>.json- pulse digests
Workflow
-
Resolve the reference point. Default: 7 days ago. Parse named anchors from the prompt:
- Calendar phrases: "last week" (7d), "last month" (30d), "last 90 days"
- Event anchors: "since I started ", "since my visit" - scan memory for the matching event date
- Absolute dates: "since 2026-04-01"
- If ambiguous, ask one clarifying question, then proceed.
-
Enumerate within the window. For each source above, list files modified or dated within the window. Don't load everything into context - stream-scan headers and key sections.
-
Classify each change. Apply the rubric in
references/clinical-significance.md:- Tier 1 - signal. New abnormal lab, med change, new diagnosis,
20% trend change in a tracked marker, new imaging finding, abnormal-to-normal resolution.
- Tier 2 - notable. Stable abnormality continuing, mild trend, new appointment scheduled, new pulse mentions of relevant topics.
- Tier 3 - noise. Routine entries, unchanged trends, low-relevance pulse items. Collapsed to a one-line count.
- Tier 1 - signal. New abnormal lab, med change, new diagnosis,
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 111 lines · 105 tokens per session scan A cdb646a45e98
memory-diff is a skill published in the GitHub repository realactivity/tula (45 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 105 tokens to every session and 1,183 once invoked, about $0.0005 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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comment-compactor
Delete the comments a diff adds unless they earn their place, and condense the few that do. Use as the final step before pushing, submitting, or finalizing a PR — after tests and lint pass, before git push / gh pr create. Also use when asked to "clean up the comments", "check the comments", or when a review flags a…
ehr-data-parsing
Parse and extract clinical data from HL7v2 messages and FHIR R4 resources using Python. Use when the user mentions HL7v2, HL7, FHIR, PID segment, OBX segment, MSH segment, Patient resource, Observation resource, Condition resource, MedicationRequest, EHR data extraction, clinical message parsing, FHIR bundle, HL7 to…
biomcp-research
Do biomedical literature and variant research with the BioMCP CLI, and file what you learn about the tool itself as issues in the biomcp repo.
system_status
Check system health -- disk usage, memory, running processes, uptime.
branch_health
Quick health check -- test counts and file stats for AIPass branches.