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identify_transform

Read-only

Test whether a sequence is a simple transform of a known OEIS sequence by applying up to three levels of common transforms and matching indexed terms; use hits to find empirical identities or extensions.

Instructions

Is this sequence a simple transform of a known OEIS sequence? A local "superseeker".

Give either terms (comma-separated, with their offset, i.e. the n of the first term) or an anum (its own terms; the entry itself is never reported). Every chain of up to depth (1-3) of ~140 primitive transforms is applied (x or / by n!, (2n)!, 2^n, n, Catalan, Bell, ...; binomial, Euler, weigh, EGF exp/log, INVERT, Stirling, Moebius and their inverses; partial sums, differences, bisections, signs, +-1, ...) and each result is looked up in the term index. Depth 1 takes about a second; depth 2 (~20k lookups) can take tens of seconds, and stops after time_budget seconds (complete=false). A hit needs a long, informative common run (>= 6 terms at depth <= 1, >= 8 at depth 2, >= 10 at depth 3) and agreement up to the end of one of the two. Each hit says which side has more terms: match_extends_query: the match continues past your terms (it may give new terms of your sequence); query_extends_match: your transformed terms continue past the match's DATA. Hits are empirical identities, to be proved before use.

Input Schema

NameRequiredDescriptionDefault
extNo
anumNo
depthNo
limitNo
termsNo
offsetNo
time_budgetNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only declare readOnlyHint/openWorldHint=false; the description adds substantial behavior on top: the depth-to-time curve, the time_budget cutoff producing complete=false, the minimum common-run thresholds per depth (6/8/10 terms), and the match_extends_query vs query_extends_match asymmetry. The closing caveat that hits are empirical identities to be proved is exactly the kind of context annotations cannot carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core question and the input modes are front-loaded, and every later sentence conveys operational information (timing, hit criteria, hit interpretation). The long parenthetical catalogue of ~140 transforms is illustrative padding that could be shortened without losing much.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 7-parameter, no-output-schema tool this covers a lot: what hits mean, how the two sides of a hit are labeled, and the timeout flag. It falls short only on the unexplained ext/limit parameters and their defaults, which an agent would need before tuning a search.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description carries the whole burden: it explains terms, offset ('the n of the first term'), anum, depth (1-3), and time_budget semantics well. However, 'ext' and 'limit' are never mentioned, and the defaults (depth 2, limit 15, offset 0) are undocumented in prose, so two of seven parameters remain opaque.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific question form ('Is this sequence a simple transform of a known OEIS sequence?') plus a memorable analogy ('A local superseeker'), so the verb+resource is unambiguous. It is clearly distinct from siblings like search_terms, guess_recurrence, and extend_from_formulas: this one applies transforms and looks each result up in the term index.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly states the two input modes ('Give either terms ... or an anum') and the cost/benefit tradeoff by depth (depth 1 ~1s, depth 2 ~20k lookups, tens of seconds). What's missing is an explicit statement of when to prefer this over search_terms or guess_recurrence, so it stops short of full alternative routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.