How do I install the Cross Source Gap Analysis skill?

Run npx skillmds@latest add nvidia/cross-source-gap-analysis in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Cross Source Gap Analysis safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Cross Source Gap Analysis?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Cross Source Gap Analysis free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Cross Source Gap Analysis?

NVIDIA (@nvidia) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Cross Source Gap Analysis by nvidia

Name: Cross Source Gap Analysis
Author: NVIDIA

File contents

cross-source-gap-analysis

Use this skill when the task is to compare or synthesize information across multiple sources rather than merely access one source.

When to use

Compare Slack discussion against GitHub issues or PRs
Compare Slack or GitHub findings against NVIDIA forum discussion
Identify missing coverage, inconsistent narratives, or follow-up areas across sources
Find external email discussions not reflected in internal meeting updates

Inputs

Load the source skills you need first:

slack-channel-summarizer
slack-channel-finder
github-readonly-live
source-etl-query
outlook-email-search

This skill does not define how to access those systems. It defines how to combine the findings once you have them.

Procedure

1. Gather the minimum useful evidence from each source

Prefer a small, relevant slice from each source over broad collection. For example:

a recent Slack window for the relevant channel
live GitHub issues or PRs from $GITHUB_READONLY_REPO, when current state matters
mirrored GitHub discussions, or historical issue/PR mirror data for the repo or feature area, when the task is about the ETL mirror or discussions
mirrored NVIDIA forum topics for the nemoclaw tag scope
recent emails filtered to the relevant project and date range

2. Normalize what each source is saying

Reduce each source to short bullets such as:

active topics
reported problems
decisions or planned work
requests for help
unresolved questions

3. Compare across sources

4. Present the result

A good default structure is:

scope and time window
what all sources agree on
gaps or mismatches
concrete follow-ups

Keep the comparison grounded in evidence from the sources you actually checked. Do not invent gaps just because one source had less data available.

Pitfalls

Do not force a gap-analysis framing when the user only asked for source access or a plain summary.
Do not over-collect. A narrow comparison is usually better than an exhaustive scrape.
Distinguish between "not discussed" and "not observed in the sampled data".
Distinguish between “not observed in the mirror” and “not present on the live source”.
Keep live GitHub REST findings separate from source ETL mirror findings when the scopes or freshness differ.

---name: cross-source-gap-analysisdescription: Compare findings across Slack, GitHub, NVIDIA forums, and Outlook to identify alignment gaps, missing coverage, and follow-ups.---# cross-source-gap-analysisUse this skill when the task is to compare or synthesize information acrossmultiple sources rather than merely access one source.## When to use- Compare Slack discussion against GitHub issues or PRs- Compare Slack or GitHub findings against NVIDIA forum discussion- Identify missing coverage, inconsistent narratives, or follow-up areas across sources- Find external email discussions not reflected in internal meeting updates## InputsLoad the source skills you need first:- `slack-channel-summarizer`- `slack-channel-finder`- `github-readonly-live`- `source-etl-query`- `outlook-email-search`This skill does not define how to access those systems. It defines how tocombine the findings once you have them.## Procedure### 1. Gather the minimum useful evidence from each sourcePrefer a small, relevant slice from each source over broad collection. For example:- a recent Slack window for the relevant channel- live GitHub issues or PRs from `$GITHUB_READONLY_REPO`, when current state matters- mirrored GitHub discussions, or historical issue/PR mirror data for the repo or feature area, when the task is about the ETL mirror or discussions- mirrored NVIDIA forum topics for the `nemoclaw` tag scope- recent emails filtered to the relevant project and date range### 2. Normalize what each source is sayingReduce each source to short bullets such as:- active topics- reported problems- decisions or planned work- requests for help- unresolved questions### 3. Compare across sources### 4. Present the resultA good default structure is:- scope and time window- what all sources agree on- gaps or mismatches- concrete follow-upsKeep the comparison grounded in evidence from the sources you actually checked.Do not invent gaps just because one source had less data available.## Pitfalls- Do not force a gap-analysis framing when the user only asked for source access or a plain summary.- Do not over-collect. A narrow comparison is usually better than an exhaustive scrape.- Distinguish between "not discussed" and "not observed in the sampled data".- Distinguish between “not observed in the mirror” and “not present on the live source”.- Keep live GitHub REST findings separate from source ETL mirror findings when the scopes or freshness differ.

Frequently asked questions

Cross Source Gap Analysis