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 nexus-labs-automation/agent-observability --skill session-conversation-trackinggit clone --depth 1 https://github.com/nexus-labs-automation/agent-observabilityWrote 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/nexus-labs-automation/agent-observability/session-conversation-tracking)<a href="https://agentmods.dev/skills/nexus-labs-automation/agent-observability/session-conversation-tracking"><img src="https://agentmods.dev/badge/skills/nexus-labs-automation/agent-observability/session-conversation-tracking/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/nexus-labs-automation/agent-observability/session-conversation-tracking"><img src="https://agentmods.dev/badge/skills/nexus-labs-automation/agent-observability/session-conversation-tracking.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 | $0.00015 | $0.01760 |
| Opus 5 | $0.00008 | $0.00880 |
| Sonnet 5 | $0.00003 | $0.00352 |
| Haiku 4.5 | $0.00002 | $0.00176 |
Grade A, and why
session-conversation-tracking 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 — 259 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Session and Conversation Tracking
Instrument sessions and conversations to understand multi-turn agent interactions.
Core Principle
Session observability answers:
- Who is the user (anonymized)?
- What's the conversation context?
- How long are sessions?
- What patterns lead to success/failure?
- Where do users drop off?
Hierarchy
User (persistent)
└── Session (single sitting)
└── Conversation (topic/thread)
└── Turn (single exchange)
└── Agent Run
├── LLM Call
└── Tool Call
Session Span Attributes
# Session identity (P0)
span.set_attribute("session.id", str(uuid4()))
span.set_attribute("session.start_time", datetime.utcnow().isoformat())
span.set_attribute("session.type", "chat") # chat, api, batch
# User context (P1 - anonymized)
span.set_attribute("user.id", hash_user_id(user_id))
span.set_attribute("user.tier", "premium") # Safe to log
span.set_attribute("user.org_id", "org_123")
# Session metadata (P1)
span.set_attribute("session.channel", "web") # web, mobile, api, slack
span.set_attribute("session.client_version", "2.1.0")
span.set_attribute("session.locale", "en-US")
Conversation Span Attributes
# Conversation identity (P0)
span.set_attribute("conversation.id", str(uuid4()))
span.set_attribute("conversation.session_id", session_id)
span.set_attribute("conversation.topic", "document_analysis")
# Turn tracking (P0)
span.set_attribute("conversation.turn_number", 5)
span.set_attribute("conversation.total_turns", 12)
# Context (P1)
span.set_attribute("conversation.messages_in_context", 10)
span.set_attribute("conversation.context_tokens", 4500)
span.set_attribute("conversation.context_window_pct", 0.15)
Turn Span Attributes
# Turn identity (P0)
span.set_attribute("turn.id", str(uuid4()))
span.set_attribute("turn.number", 5)
span.set_attribute("turn.role", "user") # user, assistant
# User input (P1 - safe metadata only)
span.set_attribute("turn.input_length", 150)
span.set_attribute("turn.input_type", "question") # question, command, feedback
span.set_attribute("turn.has_attachments", False)
# Assistant response (P1 - safe metadata only)
span.set_attribute("turn.output_length", 500)
span.set_attribute("turn.output_type", "answer")
span.set_attribute("turn.agent_runs", 1)
span.set_attribute("turn.tool_calls", 2)
span.set_attribute("turn.latency_ms", 2500)
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 · 259 lines · 15 tokens per session scan A d477d0432b22
session-conversation-tracking is a skill published in the GitHub repository nexus-labs-automation/agent-observability (7 stars, last pushed 8mo ago), licensed MIT. It adds 15 tokens to every session and 1,760 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 2026-08-31.
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