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 yeaight7/agent-powerups --skill memory-build-workflowgit clone --depth 1 https://github.com/yeaight7/agent-powerupsWrote 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/yeaight7/agent-powerups/memory-build-workflow)<a href="https://agentmods.dev/skills/yeaight7/agent-powerups/memory-build-workflow"><img src="https://agentmods.dev/badge/skills/yeaight7/agent-powerups/memory-build-workflow/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/yeaight7/agent-powerups/memory-build-workflow"><img src="https://agentmods.dev/badge/skills/yeaight7/agent-powerups/memory-build-workflow.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 | $0.00039 | $0.00676 |
| Opus 5 | $0.00019 | $0.00338 |
| Sonnet 5 | $0.00008 | $0.00135 |
| Haiku 4.5 | $0.00004 | $0.00068 |
Grade A, and why
memory-build-workflow 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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Build Workflow
Overview
Build persistent graph memory with graphify.
Use helper tools only when source format would otherwise reduce graph quality or waste context.
When to Use
- first graph build for a repo, notes folder, research corpus, or mixed raw folder
- corpus changed enough that persistent graph memory is worth refreshing
- input includes PDFs, Office docs, or noisy web pages that should be normalized before graph build
- user wants durable graph outputs instead of one-shot file reading
Do not use for:
- one small plain-text file or a narrow one-off question
- cases where an existing graph already answers the question better via query
Required Checks
apx check graphify
apx check markitdown-file-intake
apx check defuddle
Stop and report missing tools. Do not auto-install without approval.
Routing
| Situation | Action |
|---|---|
| ready local corpus of readable files | run graphify |
| existing graph plus changed sources | run graphify --update |
| PDF, Office doc, slide deck, or similar hard-to-read format | convert with markitdown-file-intake, then build with graphify |
| article or noisy web page | clean with defuddle, then build with graphify |
| user wants vault browsing after build | offer optional Obsidian export |
Core Rules
graphifyis the primary engine- prefer
graphify --updateover full rebuild when a graph already exists - use helpers only to improve source readability before graph ingestion
- keep Obsidian optional and post-build
- keep source provenance intact when converting inputs
Minimal Workflow
- Check whether a usable graph already exists.
- If it exists and sources changed, prefer
graphify --update. - If sources are noisy or binary, normalize them with the narrowest helper.
- Build or refresh with
graphify. - Offer query workflow next instead of rereading the corpus.
Common Failure Modes
- missing
graphify: stop and report; no fallback build path - rebuilding from scratch when update would work: unnecessary cost and churn
- using helpers on already-readable Markdown or code: wasted step
- treating Obsidian as required: wrong; it is optional output only
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 · 81 lines · 39 tokens per session scan A b9e3997e1af2
memory-build-workflow is a skill published in the GitHub repository yeaight7/agent-powerups (6 stars, last pushed 2d ago), licensed Apache-2.0. It adds 39 tokens to every session and 676 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 2026-09-14.
Other skills, from other repositories
persistent-notes
Save notes locally to /mnt/workspace/notes.json file. Use when user wants to "save a note" or "remember something".
session-summaries
What the chat right-panel session summary shows, what it costs, and how to make a session summarize well. Load when the user asks about the session summary panel, why a summary looks wrong or empty, or how to turn it on.
narco-check
Memory integrity audit. Detects hallucinations, circular confirmations, and state poisoning. Runs automatically after 2 consecutive failures or at nightly deep dive. Uses Opus 4.6 as the auditor model.
openlore
Query and publish to an OpenLore knowledge base over SSH using ordinary shell commands. Use when a task needs project documentation, runbooks, shared team knowledge, or a place to publish findings.
systematic-debugging
4-phase root cause debugging: understand bugs before fixing.
github-code-review
Review PRs: diffs, inline comments via gh or REST.