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 panaversity/agentfactory-business-plugins --skill workplace-searchgit clone --depth 1 https://github.com/panaversity/agentfactory-business-pluginsWrote 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/panaversity/agentfactory-business-plugins/workplace-search)<a href="https://agentmods.dev/skills/panaversity/agentfactory-business-plugins/workplace-search"><img src="https://agentmods.dev/badge/skills/panaversity/agentfactory-business-plugins/workplace-search/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/panaversity/agentfactory-business-plugins/workplace-search"><img src="https://agentmods.dev/badge/skills/panaversity/agentfactory-business-plugins/workplace-search.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 | $0.00090 | $0.00559 |
| Opus 5 | $0.00045 | $0.00280 |
| Sonnet 5 | $0.00018 | $0.00112 |
| Haiku 4.5 | $0.00009 | $0.00056 |
Grade A, and why
workplace-search 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 10d 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CROSS-CONTEXT SEARCH WORKFLOW
STEP 1 — LOAD CONTEXT
Read work.local.md in the current working directory.
If it does not exist, tell the user to run /agentic-office:setup first.
STEP 2 — SEARCH ALL LAYERS
Search across all four memory layers simultaneously:
PERSONAL: Working style; current focus; priorities TEAM: Person entries; communication notes; relationship history PROJECTS: Project names; codenames; status; decisions; milestones ORGANISATIONAL: Terminology; meeting notes; decision log; action log
STEP 3 — PRODUCE RESULTS
OUTPUT STRUCTURE:
SEARCH RESULTS: "[Query]"
================================================================
Found in:
PROJECT MEMORY:
[Relevant project entries — name; status; connection to query]
MEETING NOTES / DECISION LOG:
[Relevant decisions; when made; by whom; context]
PEOPLE MEMORY:
[Relevant person entries — role; connection to query]
TERMINOLOGY:
[Relevant term definitions]
DELEGATION LOG:
[Any active or past delegations related to query]
RECOMMENDED NEXT STEP:
[Specific actionable recommendation based on search results]
================================================================
Search Behaviour Rules
IF FOUND: Surface all relevant entries; note the layer each came from IF NOT FOUND: Say explicitly "Not in workplace memory" — do not fabricate; offer to add if the user can provide the information IF PARTIAL: Surface what exists; flag what is missing; offer to add the missing information
Cross-Reference Pattern
For queries that span multiple layers:
"What do we know about [topic]?" Search all layers simultaneously Group results by layer Synthesise: "Here is the complete picture across all memory layers"
"When did we decide [X]?" Search decision log first Cross-reference with meeting notes Surface: decision + date + context + who was involved
NEVER DO THESE
- NEVER return search results from memory you do not have — if it is not in work.local.md, say so clearly
- NEVER search only one layer when the query could span multiple
- NEVER omit the recommended next step — search without a recommended action is information without utility
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.
- 10d ago First seen · 87 lines · 90 tokens per session scan A 424d46ecae9a
workplace-search is a skill published in the GitHub repository panaversity/agentfactory-business-plugins (29 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 90 tokens to every session and 559 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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