LoggedAnalysis

This skill reads previously logged search files from the datastore and generates 3 high-level conclusions based on a user-provided assessment criteria.

It is used to summarize or interpret a day’s research activity.

When to use

Use this skill when the user asks to:

• analyse searches from a specific day
• summarize research activity
• identify trends in logged searches
• draw conclusions from prior browsing/search logs
• review what was learned on a given date

Do NOT use this skill for live web search. It only reads existing logs.

Inputs

• date (string, required) Format: YYYY/MM/DD or YYYY-MM-DD
  The day of logs to analyse.

• criteria (string, required) A short instruction describing how the logs should be assessed. Examples:

  • "Check for trends"
  • "Summarise main themes"
  • "Identify recurring interests"

• name (string, optional) Label used for the output filename.

Execution

This skill runs a Python script.

Command:

python LoggedAnalysis.py --date "" --criteria "" --name ""

Environment:

OPENCLAW_OUTPUT_ROOT optionally points to the datastore root. If not set, the skill will use the workspace root when a datastore folder exists, otherwise it falls back to C:\Users<user>.openclaw\data.

The script reads from:

/datastore/YYYY/MM/DD/

and writes to:

/analysis/YYYY/MM/DD/

Behavior

The skill:

1. Loads all .txt files from: datastore/YYYY/MM/DD/
2. Builds a compact corpus of the day’s logs
3. Applies the assessment criteria
4. Produces exactly 3 conclusions
5. Writes a JSON analysis file to: analysis/YYYY/MM/DD/

It returns:

• the 3 conclusions
• the output file path

Output

JSON object containing:

• date
• conclusions (array of 3 strings)
• output_path
• diagnostics (paths + file counts)

Examples

User:
"Analyse 2026/02/16 logs and check for trends"

→ Mechanical form:

LoggedAnalysis --date "2026/02/16" --criteria "Check for trends"

User:
"Summarise yesterday’s searches"

→ Convert to date, then call:

LoggedAnalysis --date "<resolved YYYY/MM/DD>" --criteria "Summarise main themes"

Notes

• This skill does not access the internet
• It only reads existing logs
• It is deterministic and file-backed
• It is safe to run repeatedly