Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add AgentToolkit/altk-evolve/plugin install evolve-liteWrote 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/agenttoolkit/altk-evolve/save-trajectory)<a href="https://agentmods.dev/skills/agenttoolkit/altk-evolve/save-trajectory"><img src="https://agentmods.dev/badge/skills/agenttoolkit/altk-evolve/save-trajectory/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/agenttoolkit/altk-evolve/save-trajectory"><img src="https://agentmods.dev/badge/skills/agenttoolkit/altk-evolve/save-trajectory.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 | $0.00025 | $0.01384 |
| Opus 5.5 | $0.00010 | $0.00554 |
| Sonnet 5.5 | $0.00005 | $0.00277 |
| Haiku 4.5 | $0.00003 | $0.00138 |
Grade A, and why
save-trajectory 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 16d 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.
This is a copy
98% identical to evolve-lite:save-trajectory — 5 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Save Trajectory
Overview
This skill saves the current session's conversation history as a JSON file in OpenAI chat completion format. The trajectory is saved to .evolve/trajectories/ in the project root. This enables trajectory analysis, fine-tuning data collection, and session review.
Workflow
Step 1: Walk Through Conversation Messages
Review all messages in the current conversation from start to finish. For each message, identify its type:
- User text messages
- Assistant text responses (may include thinking)
- Assistant tool calls
- Tool results
Step 2: Convert to OpenAI Chat Completion Format
Convert each message to the appropriate format:
User text message:
{"role": "user", "content": "the user's message text"}
Assistant text response (no thinking):
{"role": "assistant", "content": "the assistant's response text"}
Assistant text response (with thinking):
{"role": "assistant", "content": "the assistant's response text", "thinking": "the thinking/reasoning text"}
Assistant tool call (no visible text):
{
"role": "assistant",
"content": null,
"tool_calls": [
{
"id": "tool_call_id_here",
"type": "function",
"function": {
"name": "ToolName",
"arguments": "{\"param\": \"value\"}"
}
}
]
}
Assistant tool call with text:
{
"role": "assistant",
"content": "text before/after the tool call",
"tool_calls": [
{
"id": "tool_call_id_here",
"type": "function",
"function": {
"name": "ToolName",
"arguments": "{\"param\": \"value\"}"
}
}
]
}
Tool result:
{"role": "tool", "tool_call_id": "tool_call_id_here", "content": "the tool output text"}
Important Details
- Tool call arguments must be a JSON string, not a nested object. Use
json.dumps()on the arguments object. - Tool call IDs: Use the actual tool call ID from the conversation. If not available, generate a unique ID like
call_001,call_002, etc. - Multiple tool calls: If the assistant made multiple tool calls in one turn, include all of them in a single assistant message's
tool_callsarray, followed by separate tool result messages for each. - Thinking blocks: If the assistant had both thinking and text in the same turn, combine them into one message with both
contentandthinkingfields.
What ships with it
2 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.
- 16d ago Changed f58d36536e6d
- 2mo ago First seen · 146 lines · 25 tokens per session scan A 1e7c775e9c0e
save-trajectory is a skill published in the GitHub repository AgentToolkit/altk-evolve (135 stars, last pushed 2d ago), licensed Apache-2.0. It adds 25 tokens to every session and 1,384 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 98% identical to evolve-lite:save-trajectory, differing in 5 lines, and is treated as a copy.
save-trajectory compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| save-trajectoryAgentToolkit/altk-evolve | Skill | 135 | 2d ago | Apache-2.0 | A | 25 | Claude Code |
| memory-to-skillzilliztech/memsearch | Skill | 2.8k | yesterday | MIT | A | 82 | Claude Code, Codex |
| media-genManceRayder42/jarvis-os | Skill | 5 | 2d ago | MIT | A | 216 | Claude Code |
| research-notebookManceRayder42/jarvis-os | Skill | 5 | 2d ago | MIT | A | 130 | Claude Code |
| learnManceRayder42/jarvis-os | Skill | 5 | 2d ago | MIT | A | 121 | Claude Code |
| knowledge-packManceRayder42/jarvis-os | Skill | 5 | 2d ago | MIT | A | 72 | Claude Code |
| wiki-articleManceRayder42/jarvis-os | Skill | 5 | 2d ago | MIT | A | 70 | Claude Code |