Borrowing it
Nothing to install: this file belongs to hunter-heidenreich/academic-tools-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/hunter-heidenreich/academic-tools-mcp/main/.claude/skills/add-provider/SKILL.mdgit clone --depth 1 https://github.com/hunter-heidenreich/academic-tools-mcpWrote 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/hunter-heidenreich/academic-tools-mcp/add-provider)<a href="https://agentmods.dev/skills/hunter-heidenreich/academic-tools-mcp/add-provider"><img src="https://agentmods.dev/badge/skills/hunter-heidenreich/academic-tools-mcp/add-provider/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/hunter-heidenreich/academic-tools-mcp/add-provider"><img src="https://agentmods.dev/badge/skills/hunter-heidenreich/academic-tools-mcp/add-provider.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00046 | $0.00810 |
| Opus 5 | $0.00023 | $0.00405 |
| Sonnet 5 | $0.00009 | $0.00162 |
| Haiku 4.5 | $0.00005 | $0.00081 |
Grade A, and why
add-provider 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 3d 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 — 24 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adding a new provider or OpenAlex entity
Adding a new OpenAlex entity
- Add
_normalize_*and_canonical_*functions inproviders/openalex.py. - Add an async
get_*function that checks cache, fetches, stores. - Add focused tool(s) in the matching
tools/*.pymodule (OpenAlex metadata →tools/paper.py) that extract lean slices; shared param types live inapp.py. - Add unit tests for normalization in
tests/providers/test_openalex.py.
Adding a new API provider
Mirror providers/biorxiv.py — it is the fullest instance of the shape (both throttle wrappers, a cached_lookup getter, a PDF path). Read providers/crossref.py as a counter-example rather than a template: its rate constants are _resolve_policy() output, not literals. The shape (pooled client, _throttled_get + burst cap, _single_flight, cache → negative cache → fetch with re-checks inside the slot, 404 → negative cache) is documented in .claude/rules/providers.md and .claude/rules/net.md and .claude/rules/store.md. New clients live under providers/ and import shared infra one level up, by package (from ..net import clients, http, from ..store import cache, from ..util import config, doinorm, useragent). After mirroring it:
- Nothing to register:
stats.throttles()and the conftest reset fixture both discover the module's_throttleinstance by scanning imported modules for aThrottle-typed attribute — the name is conventional, the discovery is by type. DeclareNAMESPACEandLABELat module level and pass both to theThrottle(namespace=NAMESPACE, label=LABEL) —tests/net/test_stats.pyasserts each matches, because counters are filed under the namespace and the label is the name that reaches the agent.NAMESPACEis the on-disk.cache/directory name, so it is a data migration, not a rename — it may differ from the module name and must not be changed to follow one (providers/acl.pykeepsNAMESPACE = "acl_anthology"). UseLABELat every other site naming the provider (http.error_dict,http.parse_error_dict,stream_to_file(provider_label=)); an AST scan intests/test_politeness.pyfails on a string literal at any of them. - Add env vars to
.env.exampleand load viaconfig.get(). - If the provider serves PDFs, add a
_Routerow tomanual._ROUTES(claims,NAMESPACE,canonical_key,pdf_path) — position it before the generic-DOI fallback — and, if it also serves metadata, an entry inmanual._METADATA_SOURCE_BY_NAMESPACE. Without the row nothing routes to the new namespace. If its ids need a slash restored from a stem,corpus._restore_slashesneeds a clause too, or corpus hits won't chain back. - Add tools in the matching
tools/*.pymodule. - Tests in
tests/providers/test_<name>.py(andtests/providers/test_<name>_properties.pyfor anything hypothesis is stronger at), covering normalization, parsing, backpressure, 404 negative-cache, and TTL eviction /force_refreshif relevant.tests/mirrorssrc/; shared fakes live intests/helpers/and are imported absolutely.
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.
- 3d ago Changed d9cc4cd2f123
- 4d ago Changed · +1 lines db3215041dd3
- 5d ago First seen · 23 lines · 46 tokens per session scan A c42343f93916
add-provider is a skill published in the GitHub repository hunter-heidenreich/academic-tools-mcp (5 stars, last pushed yesterday), licensed MIT. It adds 46 tokens to every session and 810 once invoked, about $0.0002 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 2026-09-06.
Other skills, from other repositories
academic-research
Nested swiss-knife reference for academic literature work — find papers, fetch full-text PDFs, trace citations, write LaTeX manuscripts. First action for any "get me this paper" request: python3 /scripts/fetchpaper.py — walks arXiv → Unpaywall → Europe PMC → CORE → in-house publisher-page extraction…
nature-academic-search
An academic-paper search skill finds and checks research papers, preprints, clinical-trial records, and citations across sources such as PubMed, arXiv, Crossref, and OpenAlex. It can also work with identifiers such as DOI, PMID, and trial IDs.
fin-ref-paper
A reference-management tool for economics and finance research documents. It extracts citation details from research files and creates a references.bib file in formats such as BibTeX, JF, JFE, RFS, or GB/T 7714.
bibverify
Verify, repair, explain, and generate BibTeX references with Bibverify's DOI-first CLI and MCP tools.
openevidence
Query OpenEvidence (clinical evidence assistant) without an MCP server. Closely mirrors the openevidence-mcp tool surface - check auth, list question history, fetch an article, or ask a new question (with optional follow-up thread). Use when the user asks medical / evidence-based clinical questions, references…
api-data-fetcher
Fetch economic data from FRED, World Bank, and other APIs.