Agent skill

Knowledge Grounding

by Sidiora-Labs in Sidiora-Labs/centra-gideon-agent

Search the knowledge pool before answering, ground claims in retrieved sources and cite them, recognize ingest-worthy content and capture it with knowledgecreate — don't fabricate when the answer is…

Apache-2.0Auto-check passed

Install Knowledge Grounding

skills CLI
$ npx skills add Sidiora-Labs/centra-gideon-agent --skill knowledge-grounding -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Sidiora-Labs/centra-gideon-agent knowledge-grounding --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Sidiora-Labs/centra-gideon-agent.git skills-src && mkdir -p .claude/skills && cp -r skills-src/runtime/gideon/extensions/skills/bundled/knowledge-grounding .claude/skills/knowledge-grounding && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
knowledge-grounding
GitHub stars
181
Token cost
~845 tokens
SKILL.md length
434 words
Files
1
Skills in repo
24
Repo updated
First seen
Licence
Apache-2.0

At a glance

Search the knowledge pool before answering, ground claims in retrieved sources and cite them, recognize ingest-worthy content and capture it with knowledgecreate — don't fabricate when the answer is…

  • Works in 3 steps: knowledge_search with the user's… → knowledge_get the most relevant hits to… → Answer from the retrieved material, not…
  • SKILL.md covers Search before answering, Cite your sources, Don't fabricate when knowledge… and Recognize ingest-worthy content
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Knowledge Grounding is an agent skill from Sidiora-Labs/centra-gideon-agent. Search the knowledge pool before answering, ground claims in retrieved sources and cite them, recognize ingest-worthy content and capture it with knowledgecreate — don't fabricate when the answer is on record.

Its SKILL.md is about 850 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: The companion AI agent that learns, adapts and gets the work done no matter the task. The licence is Apache-2.0.

Example prompts

  • “/knowledge-grounding”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. knowledge_search with the user's question (or its key terms).
  2. knowledge_get the most relevant hits to read the actual content.
  3. Answer from the retrieved material, not from a guess.

What it can do on your machine

Read from SKILL.md and the folder at commit 2176d5b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Knowledge Grounding loads about 845 tokens when it runs. Until then it costs about 58 tokens; SKILL.md has 434 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~58
When it runs · the whole SKILL.md, loaded when a task matches
~845

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Sidiora-Labs/centra-gideon-agent at commit 2176d5b, republished under its Apache-2.0 licence (© Sidiora-Labs). 434 words, ~845 tokens.

Download SKILL.mdSave it as .claude/skills/knowledge-grounding/SKILL.md (or your agent's skills folder).
name
knowledge-grounding
description
Search the knowledge pool before answering, ground claims in retrieved sources and cite them, recognize ingest-worthy content and capture it with knowledge_create — don't fabricate when the answer is on record.
always
false
triggers
knowledge, search knowledge, what do we know, do we have, sources, cite, ingest, save to knowledge, bookmark, reference, look it up, according to

Knowledge Grounding

Gideon has a knowledge pool — ingested documents, notes, bookmarks, and references the user has accumulated. When a question might be answered by what's already on record, search it first and ground your answer in what you find rather than answering from general assumptions or making something up.

Tools: knowledge_search (semantic/keyword search), knowledge_get (fetch a specific item by id), knowledge_create (add new content to the pool).

Search before answering

For any question that could plausibly be covered by the user's own material — their projects, decisions, docs, references, prior research — knowledge_search first. If relevant items come back, base your answer on them:

  1. knowledge_search with the user's question (or its key terms).
  2. knowledge_get the most relevant hits to read the actual content.
  3. Answer from the retrieved material, not from a guess.

This is the difference between a confident-but-wrong answer and a grounded one. If the user has the answer on record, use it.

Cite your sources

When your answer rests on knowledge items, say so — name the source (title/path/id) you drew from, so the user can trust and trace it. "Per your Q2-architecture note, …" beats an unattributed assertion. If you synthesized across several items, cite each. Citations also make it obvious when an answer is grounded vs. when you're reasoning beyond the record.

Don't fabricate when knowledge exists

If the pool plausibly contains the answer, searching is mandatory before you answer from memory. Never invent a fact, a number, a decision, or a citation when the real one is retrievable. And distinguish clearly:

  • Found it → answer from the source, cite it.
  • Searched, found nothing → say the knowledge pool doesn't cover it, then answer from general reasoning labelled as such (not presented as if it came from the user's records).

Don't dress up a guess as a recalled fact.

Show full SKILL.md (134 more words)Show less

Recognize ingest-worthy content

Some content is worth keeping. When the user shares — or you produce together — something durable and reusable, capture it with knowledge_create:

  • text — a note, a decision record, a distilled summary, research findings, a snippet of reference material worth keeping.
  • bookmark — a URL/reference the user will want to find again.

Good candidates: "save this for later", a link the user clearly wants to keep, a conclusion reached after real research, reference material that answers a recurring question. Capture it so the next session can knowledge_search and find it.

Don't ingest: transient chatter, secrets, throwaway scratch, or content the user didn't signal is worth keeping. (For named, versioned generated UI/docs the user iterates on, use the artifacts skill instead; for durable user preferences and corrections, use memory-discipline. Knowledge is the searchable reference pool.)

© Sidiora-Labs, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in runtime/gideon/extensions/skills/bundled/knowledge-grounding of Sidiora-Labs/centra-gideon-agent.

Open the folder on GitHubat commit 2176d5b

Compare with similar skills

Knowledge Grounding next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Knowledge Grounding compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Knowledge Grounding this skillSidiora-Labs/centra-gideon-agent181—~845Automated safety check: PassApache-2.0
Claimsruvnet/ruflo74k2 repos~1.1kAutomated safety check: PassMIT
Iterative Retrievalaffaan-m/ECC275k7 repos~1.6kAutomated safety check: PassMIT
Grounded CitationsNousResearch/hermes-agent252k—~3.1kAutomated safety check: PassMIT
Retrieval Reflexgarrytan/gbrain31k—~735Automated safety check: PassMIT
Grounded AnswerJetXu-LLM/DocMason147—~3.1kAutomated safety check: PassApache-2.0

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Questions about Knowledge Grounding

What does Knowledge Grounding do?

Search the knowledge pool before answering, ground claims in retrieved sources and cite them, recognize ingest-worthy content and capture it with knowledgecreate — don't fabricate when the answer is…. Knowledge Grounding is an agent skill from Sidiora-Labs/centra-gideon-agent. Search the knowledge pool before answering, ground claims in retrieved sources and cite them, recognize ingest-worthy content and capture it with knowledgecreate — don't fabricate when the answer is on record.

How do I install Knowledge Grounding in Claude Code?

Run `npx skills add Sidiora-Labs/centra-gideon-agent --skill knowledge-grounding -a claude-code`. Or copy the skill folder (runtime/gideon/extensions/skills/bundled/knowledge-grounding in Sidiora-Labs/centra-gideon-agent) into .claude/skills/knowledge-grounding in your project. Claude Code loads it when a task matches its description.

How do I install Knowledge Grounding in Codex?

Run `npx skills add Sidiora-Labs/centra-gideon-agent --skill knowledge-grounding -a codex`. Or copy the skill folder (runtime/gideon/extensions/skills/bundled/knowledge-grounding in Sidiora-Labs/centra-gideon-agent) into .agents/skills/knowledge-grounding in your project. Codex loads it when a task matches its description.

Can I use Knowledge Grounding in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Sidiora-Labs/centra-gideon-agent --skill knowledge-grounding -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/knowledge-grounding, .gemini/skills/knowledge-grounding, .github/skills/knowledge-grounding and .opencode/skills/knowledge-grounding in your project.

What does Knowledge Grounding need to run?

SKILL.md names no scripts, command-line tools or credentials: Knowledge Grounding is instructions for the agent only.

Does Knowledge Grounding access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Knowledge Grounding safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Knowledge Grounding use?

Knowledge Grounding is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Knowledge Grounding use?

About 845 tokens (SKILL.md is roughly 3.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Knowledge Grounding?

Skills that share tags, products or a category with Knowledge Grounding: Claims (ruvnet/ruflo, 74k stars), Iterative Retrieval (affaan-m/ECC, 275k stars), Grounded Citations (NousResearch/hermes-agent, 252k stars) and Retrieval Reflex (garrytan/gbrain, 31k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Knowledge Grounding?

Sidiora-Labs (a GitHub organization) maintains it in Sidiora-Labs/centra-gideon-agent, which has 181 GitHub stars. The repository holds 24 skills in this directory. The repository was last updated on October 8, 2026.

Source: Sidiora-Labs/centra-gideon-agent on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.