Awesome-omni-skill chatgpt-archive-topic-background-report

Build a topic-focused research collection from ChatGPT archive viewer conversations (latest archive or all archives), run a background Responses API consolidation job with web search, and save markdown plus raw response artifacts. Use when the user asks to find archive threads by topic, reconcile repetition/contradictions, and generate a saved report with minimal polling noise.

install

source · Clone the upstream repo

git clone https://github.com/diegosouzapw/awesome-omni-skill

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skill "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/development/chatgpt-archive-topic-background-report" ~/.claude/skills/diegosouzapw-awesome-omni-skill-chatgpt-archive-topic-background-report && rm -rf "$T"

manifest: skills/development/chatgpt-archive-topic-background-report/SKILL.md

source content

ChatGPT Archive Topic Background Report

Use this skill when a user wants end-to-end topic consolidation from ChatGPT archive data:

Search relevant threads by topic in latest archive or all archives.
Assemble a deduplicated JSON research collection.
Run a background Responses API call with reasoning + verbosity + web search.
Save markdown output and response payload to disk.

Preconditions

Ensure
```
OPENAI_API_KEY
```
is set (environment or
```
.env
```
).
Ensure outbound access to
```
api.openai.com
```
is available.
Confirm
```
chatgpt_viewer_sites/
```
exists with archive folders.

Core Workflow

Run the pipeline script with topic and archive scope:

python -u .agents/skills/chatgpt-archive-topic-background-report/scripts/run_topic_report.py \
  --topic "OpenClaw / Moltbot / Clawdbot" \
  --archive-scope latest

For all archives instead of latest:

python -u .agents/skills/chatgpt-archive-topic-background-report/scripts/run_topic_report.py \
  --topic "OpenClaw / Moltbot / Clawdbot" \
  --archive-scope all

Add custom prompt constraints (topic-specific or ad hoc):

python -u .agents/skills/chatgpt-archive-topic-background-report/scripts/run_topic_report.py \
  --topic "OpenClaw / Moltbot / Clawdbot" \
  --archive-scope all \
  --ad-hoc-requirements "Prioritize security incidents and timeline precision."

Quiet Monitoring Rule

Keep polling output minimal by default.
The script prints status changes and sparse heartbeats only.
Use
```
--verbose-poll
```
only if detailed polling lines are explicitly needed.

Key Parameters

```
--archive-scope latest|all
```
: search latest archive or all archive folders.
```
--keyword-regex
```
: override keyword matching regex.
```
--keyword
```
: add extra keyword terms (repeatable).
```
--model
```
: default
```
gpt-5.2
```
.

--reasoning-effort

none|low|medium|high|xhigh

```
--verbosity
```
:
```
low|medium|high
```
.
```
--search-context-size
```
:
```
low|medium|high
```
for web search tool.

--ad-hoc-requirements

--ad-hoc-requirements-file

: append run-specific requirements.

Reporting Standard

The default developer prompt template enforces an academic/journal-style report structure.
Reports must state they are based on the provided research collection, augmented by targeted web search only when contradictions or ambiguities remain.
Reports should avoid vague, repetitive references to "the dataset" and instead use precise source-language.

Outputs

Each run writes an output directory under

scratchpad/topic_background_reports/<timestamp>_<topic>/

with:

```
assembled_dataset.json
```
(JSON artifact containing the provided research collection)
```
developer_prompt_effective.txt
```
```
user_task_effective.txt
```
```
report.md
```
```
response_payload.json
```
```
run_manifest.json
```

Bundled Resources

```
scripts/run_topic_report.py
```
: complete pipeline (assemble -> background API -> poll -> save outputs).

references/developer_prompt_template.txt

: base developer prompt template with

{{TOPIC}}

placeholder.