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/razaib-khan/forgeweave/memory-managernpx skills add Razaib-khan/ForgeWeave --skill memory-managergit clone --depth 1 https://github.com/Razaib-khan/ForgeWeaveWrote 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/razaib-khan/forgeweave/memory-manager)<a href="https://agentmods.dev/skills/razaib-khan/forgeweave/memory-manager"><img src="https://agentmods.dev/badge/skills/razaib-khan/forgeweave/memory-manager.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 | $0.00017 | $0.00540 |
| Opus 5 | $0.00009 | $0.00270 |
| Sonnet 5 | $0.00003 | $0.00108 |
| Haiku 4.5 | $0.00002 | $0.00054 |
Grade A, and why
Memory Manager 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 4d 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Manager
Purpose
Persist and retrieve structured data across sessions — research outputs, intermediate reasoning steps, reusable knowledge chunks, and cache entries. Prevents redundant work by reusing previously computed results when inputs match.
When to Use
- Research results should be saved for future reference
- Intermediate reasoning needs to be persisted for multi-step workflows
- Previously computed results can be reused instead of recomputed
- Debug or trace information needs to be logged
When Not to Use
- The data is ephemeral and only needed for the current response
- The data contains secrets or credentials (use secure storage instead)
- The storage would exceed reasonable size limits
Inputs
| Input | Type | Required | Description |
|---|---|---|---|
operation |
enum | Yes | save, load, search, clear |
key |
string | Depends | Unique key for the data |
data |
object | For save | The data to persist |
namespace |
string | No (default: general) | Category for the data |
Expected Outputs
| Output | Description |
|---|---|
| Operation result | Success with location, or loaded data, or search results |
Exact Workflow Steps
- Determine the persistence location based on namespace and TUI
- For save: serialize data to disk at
research/or.<tui>/memory/ - For load: deserialize data from its persisted location
- For search: scan persisted data for matching keys or content
- For clear: remove caches and temporary data
Required Checks
- Saved data is retrievable with the correct key
- Cache entries have expiration or size limits
- No sensitive data is persisted without warning
Failure Modes
| Failure Condition | Response |
|---|---|
| Key not found on load | Report "not found" |
| Storage full | Suggest clearing old entries |
| Serialization fails | Report the unsupported type |
References
| Reference | Path |
|---|---|
| Cache & Store skill | ../cache-store/SKILL.md |
| research/ directory | ./research/ |
What ships with it
2 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.
- 4d ago First seen · 80 lines · 17 tokens per session scan A ebd31bdf9537
Memory Manager is a skill published in the GitHub repository Razaib-khan/ForgeWeave (1 stars, last pushed 2mo ago), licensed MIT. It adds 17 tokens to every session and 540 once invoked, about $0.0001 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
memory
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cache
Use when the user wants to view, search, add, edit, prune, archive, or clear hyperflow memory entries. CRUD interface for .hyperflow/memory/ — never modifies source code, only memory files. Trigger with /hyperflow:cache, "show memory", "search memory for X", "clear memory", "what does hyperflow remember about Y".
digital-brain
This skill should be used when the user asks to "write a post", "check my voice", "look up contact", "prepare for meeting", "weekly review", "track goals", or mentions personal brand, content creation, network management, or voice consistency.
hive.context-preservation
Proactively extract critical values from tool results into working notes before automatic context pruning destroys them.
hive.note-taking
Maintain a free-form scratchpad of decisions, extracted values, and open questions so context pruning doesn't lose anything you still need.
recall-memory
Recall relevant long-term memories on demand. Given a topic or question, judges relevance from pre-loaded metadata, loads only relevant files, and returns a concise summary to the main agent.