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/practicalswan/agent-skills/serena-usagenpx skills add PracticalSwan/agent-skills --skill serena-usagegit clone --depth 1 https://github.com/PracticalSwan/agent-skillsWrote 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/practicalswan/agent-skills/serena-usage)<a href="https://agentmods.dev/skills/practicalswan/agent-skills/serena-usage"><img src="https://agentmods.dev/badge/skills/practicalswan/agent-skills/serena-usage.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 | $0.00040 | $0.06530 |
| Opus 5 | $0.00020 | $0.03265 |
| Sonnet 5 | $0.00008 | $0.01306 |
| Haiku 4.5 | $0.00004 | $0.00653 |
Grade A, and why
serena-usage 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 today.
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 — 705 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Serena Usage
Effective usage of the Serena MCP Server for project memory management, code intelligence, and maintaining continuity across AI agent sessions.
- Leverage native parallel subagent dispatch and 200k+ context windows where available.
Activation Conditions
Use symptom -> action triggers: when one matches, apply this skill and verify with the protocol below.
MUST activate when:
- Serena is available for the project
- Task requires project memory continuity
- Task requires symbol navigation or Serena refactoring workflow
- Managing project memories for AI session continuity
- Navigating codebases using symbol-based tools
- Performing code refactoring with Serena's symbol management
- Setting up Serena onboarding for new projects
- Using Serena's memory system for project context preservation
Critical: Always verify project activation FIRST with get_current_config before any Serena operations
Prerequisites
- Serena MCP Server configured and running
- Project activated (use
get_current_configto verify, oractivate_projectif not activated) - Onboarding completed for the target project (use
check_onboarding_performedfirst) - If not activated, run
activate_projectwith project name or path - If not onboarded, run
onboardingtool after activation
Onboarding Workflow
First-Time Project Setup
- Check activation: Call
get_current_configto verify if project is activated - Activate if needed: If not activated, call
activate_projectwith project name or path - Check onboarding: Call
check_onboarding_performedto verify onboarding status - Read manual: If not onboarded, call
initial_instructionsto read the Serena Instructions Manual - Initialize: Call
onboardingto complete project setup - Serena analyzes the project structure and creates initial context
What Onboarding Captures
- Project language and framework detection
- Directory structure analysis
- Key file identification
- Symbol index creation
- Initial memory scaffolding
What ships with it
6 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.
- today Changed dcc45bc95680
- 3d ago First seen · 705 lines · 40 tokens per session scan A 8109cecd0099
serena-usage is a skill published in the GitHub repository PracticalSwan/agent-skills (13 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 6,530 once invoked, about $0.0002 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 2026-09-03.
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