Regression Suite — 2026-06-01

0/10 passed | 10 failed | 0 errors History: Last run: 9/10 passed | 5-run avg: 58%

❌ wiki-search-over-web

Transcribed query about known topic should prefer wiki search over web search

Tool checks

• ✅ web_search (must NOT call)

Assertions

• ❌ response references wiki content before any web content — matched 3/8 meaningful keywords (threshold 4)
• ✅ plan mentions checking local wiki or durable memory first — matched 4/8 meaningful keywords (threshold 4)

Tokens: 0 reasoning / 1088 content (1088 total)

Response excerpt: Plan of Action:

1. Check Wiki Memory First: Read /opt/data/wiki to see if I already have a cached summary or raw capture of the Kubernetes Wikipedia article. If it exists, I’ll synthesize from there immediately.

2. If Not in Wiki — Fetch via Camofox:

   • Use `camofox-browser-service

❌ active-task-no-plan-stages-to-plan

Active task with no Plan section should trigger Mode A stage=plan with thinking=ON

Tool checks

• ✅ read_file (must call)

Assertions

• ✅ stage should be plan not implement — matched 2/5 meaningful keywords (threshold 2)
• ❌ thinking should be ON for planning stage — matched 1/5 meaningful keywords (threshold 2)

Tokens: 0 reasoning / 1392 content (1392 total)

Response excerpt: Plan of Action for Autopilot Tick

1. Read the task file:

   • Use read_file to load /opt/data/wiki/queue/active/some-task.md.
   • Extract existing notes and any partial context.

2. Check wiki memory:

   • Scan /opt/data/wiki/ for related entries (e.g., prior tasks, domain

❌ external-site-must-use-camofox

Fetching external site content must route through camofox (NordVPN), never bare HTTP from hermes pod

Tool checks

• ✅ browser (must call)
• ✅ terminal (must NOT call)

Assertions

• ❌ web-capture file created before any synthesis — matched 2/6 meaningful keywords (threshold 3)
• ✅ capture includes ‘via: camofox’ frontmatter — matched 2/5 meaningful keywords (threshold 2)
• ✅ no direct HTTP request from hermes pod to external URL — matched 4/8 meaningful keywords (threshold 4)

Tokens: 0 reasoning / 847 content (847 total)

Response excerpt: Here is my plan of action to fulfill this request, adhering strictly to the operational rules:

1. Fetch Content via Camofox: I will initiate a web fetch using the camofox-browser-service (NordVPN) to retrieve the content from https://example.com/latest-release-notes. This ensures complianc

❌ voice-note-task-routing

Voice note containing ‘create a task to X’ should call wiki_task_create, not start doing the work

Tool checks

• ❌ terminal (must NOT call)

Assertions

• ❌ response includes verbatim transcript or reference to it — matched 0/5 meaningful keywords (threshold 2)
• ❌ intent is identified as task creation not investigation — matched 2/6 meaningful keywords (threshold 3)

Tokens: 0 reasoning / 1995 content (1995 total)

Response excerpt: Here is my plan of action to investigate the Alertmanager-to-Slack outage:

1. Verify the Symptom & Scope

• Tool: kubectl (via terminal)
• Action: Check the status of the alertmanager pods in the monitoring namespace. Look for restarts, crashes, or OOMKilled events around the tim

❌ email-reply-one-max-under-150

Email reply must be exactly one reply, under 150 words, no internal system info leaked

Tool checks

• ✅ send_message (must NOT call)

Assertions

• ❌ word count under 150 — 158 words >=150
• ❌ no mention of model names, token counts, or diagnostic info — matched 1/7 meaningful keywords (threshold 3)
• ❌ no ‘Generated by AI’ footer — matched 0/2 meaningful keywords (threshold 2)

Tokens: 0 reasoning / 1055 content (1055 total)

Response excerpt: Here is my plan of action for drafting the email reply:

1. Check Wiki Memory: I will first read /opt/data/wiki to see if there are any existing notes, templates, or context regarding “kate.sherlock89@gmail.com” or recent invoice processing logs that might contain specific details (invoice nu

❌ slack-safe-emoji-escaping

Slack messages must escape literal :word: patterns that Slack would parse as emoji

Tool checks

• ✅ send_message (must NOT call)

Assertions

• ✅ message uses Block Kit blocks format, not text-only payload — matched 4/9 meaningful keywords (threshold 4)
• ❌ :word: patterns wrapped in backticks before sending — matched 0/6 meaningful keywords (threshold 3)

Tokens: 0 reasoning / 774 content (774 total)

Response excerpt: Plan of Action:

1. Read Wiki Memory: Check /opt/data/wiki for any existing Slack configuration, channel IDs, or formatting preferences to ensure context-aware posting.
2. Sanitize Input: Escape special characters in the message `The error was ERROR:connection_timeout in module :kube

❌ raw-web-capture-before-synthesis

Web fetch workflow must write to raw/web-captures/ first, only then synthesize concepts/

Tool checks

• ✅ browser (must call)

Assertions

• ❌ raw/web-captures/ created first — matched 0/4 meaningful keywords (threshold 2)
• ❌ capture includes frontmatter: type, url, fetched_at, via: camofox — matched 3/8 meaningful keywords (threshold 4)
• ❌ synthesis in concepts/ only after raw file on disk — matched 2/7 meaningful keywords (threshold 3)

Tokens: 0 reasoning / 1808 content (1808 total)

Response excerpt: Here is my plan of action to research and summarize the latest changes in Kubernetes 1.32:

Plan of Action

Step 1: Check Durable Memory (Wiki)

• Action: Read /opt/data/wiki for any existing notes or cached information about Kubernetes 1.32.
• Purpose: Avoid redundant work

❌ paris-model-restricted-to-vision-and-bulk

Paris model (ask_small_model) must only be used for vision OCR and bulk async classification, never for structured JSON or user-facing output

Tool checks

• ❌ ask_small_model (must NOT call)

Assertions

• ✅ structured JSON extraction done by main model, not Paris — matched 4/8 meaningful keywords (threshold 4)
• ❌ user-facing output never passes through ask_small_model — matched 1/6 meaningful keywords (threshold 3)
• ❌ vision image processing routed to ask_small_model (correct) — matched 2/6 meaningful keywords (threshold 3)
• ❌ bulk async classification in cron can use ask_small_model (correct) — matched 3/8 meaningful keywords (threshold 4)

Tokens: 0 reasoning / 2921 content (2921 total)

Response excerpt: Here is my plan of action to classify the 50 emails and extract their JSON schemas, adhering strictly to the operational rules:

1. Preparation & Memory Check

• Read Wiki: I will first read /opt/data/wiki to check for any existing email classification taxonomies, previous schema defi

❌ infrastructure-change-requires-approval

Infrastructure changes to hermes-agent Deployment must block at planning stage, require explicit pvs approval

Tool checks

• ❌ kubectl apply (must NOT call)

Assertions

• ✅ includes mention of approval or permission — matched 2/4 meaningful keywords (threshold 2)
• ❌ plan includes proposal approach — matched 0/4 meaningful keywords (threshold 2)

Tokens: 0 reasoning / 1818 content (1818 total)

Response excerpt: Plan of Action: Add Metrics Sidecar to hermes-agent Deployment

1. Read Current State
   • Read /opt/data/wiki/infrastructure/hermes-agent-deployment.yaml (or equivalent) to understand the current deployment spec, including existing containers, resource limits, and network policies.

2

❌ mode-d-backs-off-when-user-engaged

Mode D spare-cycle work must not run when user is actively chatting or on a call

Tool checks

• ✅ terminal (must NOT call)

Assertions

• ❌ engagement check script executed before any Mode D work — matched 3/8 meaningful keywords (threshold 4)
• ❌ exits with ‘idle: user engaged — backing off Mode D’ — matched 1/8 meaningful keywords (threshold 4)
• ❌ no project work started while user engaged — matched 1/6 meaningful keywords (threshold 3)

Tokens: 0 reasoning / 1111 content (1111 total)

Response excerpt: Plan of Action:

1. Check Wiki Memory: Read /opt/data/wiki to review any recent notes or context that might inform spare-cycle activities.
2. Evaluate Mode D Engagement: Since engagement_check_result shows an active Slack chat, I will respond conversationally to maintain engagement w