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.
git clone --depth 1 https://github.com/WYRE-AI/msp-claude-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/commands/wyre-ai/msp-claude-plugins/training-status)<a href="https://agentmods.dev/commands/wyre-ai/msp-claude-plugins/training-status"><img src="https://agentmods.dev/badge/commands/wyre-ai/msp-claude-plugins/training-status/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/commands/wyre-ai/msp-claude-plugins/training-status"><img src="https://agentmods.dev/badge/commands/wyre-ai/msp-claude-plugins/training-status.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 | $0.00020 | $0.00842 |
| Opus 5.5 | $0.00008 | $0.00337 |
| Sonnet 5.5 | $0.00004 | $0.00168 |
| Haiku 4.5 | $0.00002 | $0.00084 |
Grade A, and why
training-status 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 2mo 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Training Status
Run the training-completion sweep used by the training-compliance-auditor
agent: per-campaign completion rates, named overdue users with days overdue,
and cadence-compliance status where the expected training cadence is known
— for one client, or across the whole portfolio if client is omitted.
Prerequisites
- Conduit gateway connected (
conduit) - No specific vendor is required — clients with zero connected training/awareness tooling are still included in the output, flagged as unmeasured rather than excluded
Steps
-
Establish scope. If
clientis provided, resolve it against the PSA/tenant list and scope the run to that one client. If omitted, run portfolio-wide across every client. -
Discover connected tooling per client. Call
conduit__search_toolsscoped to the run. KnowBe4 is the primary training/phishing-simulation source; Proofpoint and Checkpoint Avanan are optional secondary sources of awareness-adjacent signal where connected. Any client with zero connected training/awareness tooling is flagged immediately as unmeasured. -
Pull campaign and completion data for every client with connected tooling, per the
training-completion-trackingskill. -
Compute per-campaign completion rates and identify overdue users, named individually with days overdue, not just an aggregate percentage.
-
Apply cadence-compliance judgment only where the expected cadence is known (documentation, PSA contract, or explicit input). Where unknown, report completion status without a cadence verdict and say so.
-
Surface unmeasured clients prominently, separate from the completion detail, rather than letting them read as compliant by omission.
Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| client | string | No | (omit for portfolio-wide) | Client/tenant name or ID to scope the training snapshot to a single client |
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.
- 2mo ago First seen · 119 lines · 20 tokens per session scan A 481827d19aa7
training-status is a command published in the GitHub repository WYRE-AI/msp-claude-plugins (52 stars, last pushed yesterday), licensed Apache-2.0. It adds 20 tokens to every session and 842 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 2026-09-04.
training-status compared with commands from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| training-statusWYRE-AI/msp-claude-plugins | Command | 52 | yesterday | Apache-2.0 | A | 20 | Claude Code |
| checklistgithub/spec-kit | Command | 148k | yesterday | MIT | A | 13 | Claude Code |
| clarifygithub/spec-kit | Command | 148k | yesterday | MIT | A | 27 | Claude Code |
| specifygithub/spec-kit | Command | 148k | yesterday | MIT | A | 13 | Claude Code |
| analyzegithub/spec-kit | Command | 148k | yesterday | MIT | A | 26 | Claude Code |
| convergegithub/spec-kit | Command | 148k | yesterday | MIT | A | 35 | Claude Code |
| implementgithub/spec-kit | Command | 148k | yesterday | MIT | A | 14 | Claude Code |