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 ani3198/threadbase --skill threadbase-workflowgit clone --depth 1 https://github.com/ani3198/threadbaseWrote 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/ani3198/threadbase/threadbase-workflow)<a href="https://agentmods.dev/skills/ani3198/threadbase/threadbase-workflow"><img src="https://agentmods.dev/badge/skills/ani3198/threadbase/threadbase-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/ani3198/threadbase/threadbase-workflow"><img src="https://agentmods.dev/badge/skills/ani3198/threadbase/threadbase-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 | $0.00027 | $0.00559 |
| Opus 5.5 | $0.00011 | $0.00224 |
| Sonnet 5.5 | $0.00005 | $0.00112 |
| Haiku 4.5 | $0.00003 | $0.00056 |
Grade A, and why
threadbase-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 1mo 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threadbase Workflow
Use this skill when:
- the user wants to set up Threadbase in the current repository
- the repository already contains
.ai/Threadbase files .ai/generated/context.mdis missing, empty, or stale- you need to record decisions, changes, requirements, or issues in shared repo memory
Core Model
- Treat
.ai/memory/*as the source of truth. - Treat
.ai/generated/context.mdas derived output. - Keep memory human-readable and markdown-first.
- Never store secrets, credentials, or tokens in Threadbase files.
Setup
- Work from the actual repository root or the agent workspace root for the project.
- If Threadbase is not initialized yet, prefer:
threadbase init
- If
threadbaseis not available onPATH, fall back to:
npx threadbase init
- If the user wants the generated files to stay local and untracked, use:
threadbase init --local
First Session
- Read
.ai/rules.md. - Read
.ai/generated/context.md. - If
.ai/generated/context.mdis missing or empty:- read
.ai/prompts/generate_context.md - inspect the repository directly
- generate the first
.ai/generated/context.mdfrom scratch - include YAML frontmatter with
generated_atandsource_file_count
- read
If memory files already exist under .ai/memory/*, use them as the authoritative input when generating context.
During Work
- Read
.ai/generated/context.mdbefore meaningful implementation changes. - If the context looks stale, regenerate it from
.ai/memory/*. - Follow any additional project rules found in
AGENTS.mdand.ai/rules.md.
After Work
Record meaningful updates in one or more of:
.ai/memory/decisions/.ai/memory/changes/.ai/memory/requirements/.ai/memory/issues/
For new memory entries:
- Use one markdown file per item.
- Prefer filenames like
YYYYMMDD-HHMM-short-slug.md. - Include frontmatter with:
idtypecreated_atsummary
- Include body sections:
## Context## Details
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.
- 1mo ago First seen · 84 lines · 27 tokens per session scan A 2558e1dca42d
threadbase-workflow is a skill published in the GitHub repository ani3198/threadbase (4 stars, last pushed 4mo ago), licensed MIT. It adds 27 tokens to every session and 559 once invoked, about $0.0001 per session on Opus 5.5. 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
mem0-oss-to-platform
Plan, then execute, a migration of a project from the mem0 open-source / self-hosted SDK (local Memory class) to the mem0 Platform / hosted SDK (MemoryClient). TRIGGER when: the developer wants to move, switch, or migrate mem0 off OSS/self-hosted to the hosted API, e.g. "migrate my mem0 setup to the platform", "switch…
forget
Remove a personal fact, preference, relationship detail, topic, or prior event from Muse's active memory and stop existing copies or automations from bringing it back. Use for explicit requests such as 'forget that', 'don't remember this about me', or 'remove that from your memory'. Do not use when 'forget it' merely…
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.