Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add sparq-org/sparq --skill agent-toolsgit clone --depth 1 https://github.com/sparq-org/sparqWrote 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/sparq-org/sparq/agent-tools)<a href="https://agentmods.dev/skills/sparq-org/sparq/agent-tools"><img src="https://agentmods.dev/badge/skills/sparq-org/sparq/agent-tools.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 52 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00618 | $0.07560 |
| Opus 5 | $0.00309 | $0.03780 |
| Sonnet 5 | $0.00124 | $0.01512 |
| Haiku 4.5 | $0.00062 | $0.00756 |
Grade A, and why
agent-tools 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 392 lines — stays where its author put it; the contents beside it link to each section on GitHub.
sparq agent-tools (MCP)
The MCP front door of the sparq RDF + SPARQL engine: the opt-in sparq-mcp
crate turns a loaded sparq_core::Graph into a Model Context Protocol server so an
LLM/agent can use the dataset as first-class tools.
It is opt-in (a separate crate; nothing in the workspace depends on it, the default
engine build does not compile it) and a thin wrapper over existing surfaces — it adds
no engine capability. JSON-RPC 2.0 framing is hand-rolled over serde_json; there is no
heavy MCP-SDK dependency.
Tools
| tool | wraps | returns |
|---|---|---|
query |
sparq_engine::query_json (SELECT/ASK) |
SPARQL 1.1 Query Results JSON |
construct |
sparq_engine::construct_ntriples (CONSTRUCT/DESCRIBE) |
N-Triples text |
introspect |
sparq_introspect::Introspection |
effective schema — JSON or token-budgeted text |
shapes |
sparq_introspect::Introspection (per-class) |
data-grounded SHACL-style shape for one class IRI |
stats |
graph count + introspection totals | small JSON object |
classes |
sparq_introspect::Introspection |
class IRIs + instance and predicate counts, largest first |
prefixes |
sparq_introspect::Introspection |
namespace declarations + distinct IRI term counts, largest first |
void |
sparq_introspect::Introspection |
W3C VoID N-Triples; optional characteristic sets |
ask (feature nlq, OFF by default) |
sparq_nlq NL→SPARQL loop |
executed SPARQL + real result rows (+ citations) |
nl_query (feature nlq, OFF by default) |
sparq_nlq grounding + spargebra validation, no execution |
validated SPARQL, executed: false, no rows |
update (gated, OFF by default) |
sparq_engine::update_in_place_atomic |
new triple count |
template_list / template_invoke (feature templates, OFF by default) |
sparq_engine::templates (#901 injection-safe binding) |
definitions / typed fail-closed invocation |
text_search (feature text, OFF by default) |
sparq_text::TextIndex (BM25, lazily built + reconciled) |
ranked literal hits JSON |
validate (feature shacl, OFF by default) |
sparq_shacl::validate |
{conforms, results} JSON |
describe_form (feature shacl, OFF by default) |
sparq_forms::derive_form |
FormDescription JSON, verbatim |
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.
- 4d ago Changed f6f23334507c
- 7d ago First seen · 392 lines · 618 tokens per session scan A 509875a97ce8
agent-tools is a skill published in the GitHub repository sparq-org/sparq (10 stars, last pushed 2d ago), licensed MIT. It adds 618 tokens to every session and 7,560 once invoked, about $0.0031 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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