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.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 5.1 | $0.00020 | $0.00842 |
| Opus 5 | $0.00010 | $0.00421 |
| Sonnet 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 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 — 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.
- 4d 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 (45 stars, last pushed 5d ago), licensed Apache-2.0. It adds 20 tokens to every session and 842 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 2026-09-04.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.