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 MereWhiplash/engram-cogitator --skill remembergit clone --depth 1 https://github.com/MereWhiplash/engram-cogitatorWrote 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/merewhiplash/engram-cogitator/remember)<a href="https://agentmods.dev/skills/merewhiplash/engram-cogitator/remember"><img src="https://agentmods.dev/badge/skills/merewhiplash/engram-cogitator/remember.svg" alt="Measured on agentmods" 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 | $0.00041 | $0.00814 |
| Opus 5 | $0.00020 | $0.00407 |
| Sonnet 5 | $0.00008 | $0.00163 |
| Haiku 4.5 | $0.00004 | $0.00081 |
Grade A, and why
remember 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 8d 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 — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Storing Memories
Use the 2-of-3 rule. Store if at least TWO are true:
- Future sessions - Will this matter when returning to this project?
- Project-specific - Is this unique to this codebase?
- Costly to rediscover - Would finding this again waste time or tokens?
Memory Types
| Type | Use for | Examples |
|---|---|---|
decision |
Architectural choices, why X over Y | "Chose Redis over Memcached because..." |
learning |
Codebase discoveries, gotchas, workarounds | "API rate limits are 100 req/min..." |
pattern |
Recurring conventions in this project | "All API responses use envelope format..." |
config |
Project configuration (managed by @cog-init/@config) | Test commands, branching conventions |
Before Storing
1. Search First
ec_search:
query: [what you want to store]
Avoid duplicates. If similar exists, consider updating instead.
2. Evaluate Worth
Store:
- Architectural decisions with rationale
- Non-obvious gotchas that cost time
- Project-specific conventions
- Integration quirks with external services
Skip:
- Obvious things (syntax, common patterns)
- Temporary fixes or WIP
- Things easily found in docs
- Generic programming knowledge
Storing
Use ec_add with required fields:
ec_add:
type: decision|learning|pattern
area: [component like "auth", "api", "database"]
content: [1-2 sentences, specific and actionable]
rationale: [Why this matters, optional but recommended]
Good vs Bad Examples
Decisions
GOOD:
type: decision
area: auth
content: Using JWT with short-lived access tokens (15min) and refresh tokens (7d) for session management
rationale: Balance between security (short access) and UX (don't require frequent re-login)
BAD:
type: decision
area: auth
content: Using JWT for authentication
rationale: It's popular
Learnings
GOOD:
type: learning
area: api
content: External payment API returns 200 with error in body for validation failures. Must check response.success field, not just HTTP status.
rationale: Discovered during integration - caused silent failures initially
BAD:
type: learning
area: api
content: API sometimes fails
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.
- 8d ago First seen · 134 lines · 41 tokens per session scan A b3eda3fdeb02
remember is a skill published in the GitHub repository MereWhiplash/engram-cogitator (4 stars, last pushed 2mo ago), licensed MIT. It adds 41 tokens to every session and 814 once invoked, about $0.0002 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 2026-08-31.
Other skills, from other repositories
media-ingest
Ingest video, audio, PDF, book, screenshot, and GitHub repo content into the brain. Multi-format handling with entity extraction and backlink propagation. Covers video-ingest, youtube-ingest, and book-ingest subtypes.
mem0-oss-to-platform
Plan and then execute a migration of a project from the mem0 open-source / self-hosted SDK (the local Memory class) to the mem0 Platform / hosted / managed SDK (the MemoryClient class). Use this whenever a developer wants to move, switch, or migrate their mem0 usage off OSS/self-hosted to the hosted API — e.g.…
Cortex
Operate Cortex, the LifeOS memory system — the typed Knowledge Archive (People, Companies, Ideas, Research with typed related: links) plus recall of prior work sessions, ISAs, and conversations. Search, add, harvest, develop, ingest, distill, graph-navigate, recall. USE WHEN cortex, knowledge, knowledge base, search…
memory
Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.
ha-data-stores
Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…
establishing-project-context
Use when the user asks to establish shared project language, or project work exposes a conflicting, renamed, or deprecated domain term that needs active semantic modeling. Routine small tasks stay on the fast path.