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 agentmods add skills/apiliumcode/mayros/workflow-insightsnpx skills add ApiliumCode/mayros --skill workflow-insightsgit clone --depth 1 https://github.com/ApiliumCode/mayrosWhat 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 | $0.00016 | $0.00487 |
| Opus 5 | $0.00008 | $0.00244 |
| Sonnet 5 | $0.00003 | $0.00097 |
| Haiku 4.5 | $0.00002 | $0.00049 |
Grade A, and why
workflow-insights 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 2d 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 — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
workflow-insights
Detect anti-patterns in agent workflows and compute health scores based on 7 weighted pattern detectors.
When to Use
Use when analyzing agent execution traces, debugging sluggish workflows, or auditing multi-step agent pipelines for inefficiency. The skill evaluates delegation chains, error patterns, resource usage, and tool utilization to produce a 0-100 health score.
Anti-Pattern Detectors
| # | Pattern | Weight | Description |
|---|---|---|---|
| 1 | Repeated Failure | 20 | Same error appearing 3+ times suggests retry without fix |
| 2 | Long Chain | 15 | Delegation chain exceeding 5 steps suggests over-decomposition |
| 3 | Unused Tool | 5 | Tool registered but never called suggests bloated configuration |
| 4 | Redundant Query | 10 | Same query pattern appearing multiple times suggests missing caching |
| 5 | Timeout Pattern | 20 | Multiple timeouts in sequence suggests resource contention |
| 6 | Resource Waste | 15 | Large context sent to simple tasks suggests poor task routing |
| 7 | Error Cascade | 15 | Error in one step causing errors in 3+ downstream steps suggests missing error boundaries |
Health Score
- 80-100: Healthy
- 60-79: Needs attention
- 40-59: Degraded
- 0-39: Critical
Instructions
- Recall previous workflow analysis with
skill_memory_contextusing predicateworkflow:analysis - The skill scans query results for the 7 anti-pattern indicators listed above
- Each detected pattern reduces the health score by its weight (starting from 100)
- Review detected anti-patterns and address the highest-weight issues first
- Re-run periodically to track workflow health improvements over time
What ships with it
9 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.
- 2d ago First seen · 50 lines · 16 tokens per session scan A 68675bf000f9
workflow-insights is a skill published in the GitHub repository ApiliumCode/mayros (12 stars, last pushed 1mo ago), licensed MIT. It adds 16 tokens to every session and 487 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 2026-08-30.
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